To see the other types of publications on this topic, follow the link: Single objective.
Dissertations / Theses on the topic 'Single objective'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 dissertations / theses for your research on the topic 'Single objective.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse dissertations / theses on a wide variety of disciplines and organise your bibliography correctly.
1
Lidberg, Simon. "Evolving Cuckoo Search : From single-objective to multi-objective." Thesis, Högskolan i Skövde, Institutionen för teknik och samhälle, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-5309.
Full textAbstract:
This thesis aims to produce a novel multi-objective algorithm that is based on Cuckoo Search by Dr. Xin-She Yang. Cuckoo Search is a promising nature-inspired meta-heuristic optimization algorithm, which currently is only able to solve single-objective optimization problems. After an introduction, a number of theoretical points are presented as a basis for the decision of which algorithms to hybridize Cuckoo Search with. These are then reviewed in detail and verified against current benchmark algorithms to evaluate their efficiency. To test the proposed algorithm in a new setting, a real-world combinatorial problem is used. The proposed algorithm is then used as an optimization engine for a simulation-based system and compared against a current implementation.
2
Gorski, Jochen [Verfasser]. "Multiple Objective Optimization and Implications for Single Objective Optimization / Jochen Gorski." Aachen : Shaker, 2010. http://d-nb.info/1084536323/34.
Full text
3
Tsang, Wai-pong Wilburn, and 曾瑋邦. "Bio-inspired algorithms for single and multi-objective optimization." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B42182104.
Full text
4
Tsang, Wai-pong Wilburn. "Bio-inspired algorithms for single and multi-objective optimization." Click to view the E-thesis via HKUTO, 2009. http://sunzi.lib.hku.hk/hkuto/record/B42182104.
Full text
5
Copado, Méndez Pedro Jesús. "Contribution to the development of efficient algorithms for solving complex single-objective and multi-objective optimization models." Doctoral thesis, Universitat Rovira i Virgili, 2014. http://hdl.handle.net/10803/284089.
Full textAbstract:
L’optimització en enginyeria de processos és un àrea molt estesa que ha anat evolucionant al llarg del temps i ha passat de ser una metodologia d'interès purament acadèmic a una tecnologia que té, i que contínua tenint, gran impacte en la indústria. En aquesta tesi ens hem centrat en el desenvolupament mètodes basats en dues eines típiques d'optimització: programació matemàtica i metaheurístiques. Els objectius d'aquesta tesi són: el primer és desenvolupar una metaheuristica híbrida per a l'optimització del disseny de cadenes de subministrament, d'un sol objectiu (cost o benefici), on tots els paràmetres són coneguts a priori; el segon és desenvolupar un algorisme efectiu per a reducció d'objectius facilitant la resolució de problemes multi-objectiu; i finalment s'han implementat una sèrie de millores en el mètode de la restricció èpsilon per millorar l'eficiència en la resolució de problemes multi-objectiu. Tots els algorismes presentats han estat comparats i avaluats amb els mètodes establerts per la literatura.<br>La optimización en ingeniería de procesos es un área muy extensa que ha ido evolucionando a lo largo del tiempo y ha pasado de ser una metodología de interés puramente académico a una tecnología que tiene, y que continua teniendo, gran impacto en la industria. En esta tesis nos hemos centrado en el desarrollo de métodos basados en dos herramientas típicas de optimización: programación matemática y metaheurísticas. Los objetivos de esta tesis son: el primero es desarrollar una metaheuristica híbrida para la optimización del diseño de cadenas de suministro, de un solo objetivo (coste o beneficio), donde todos los parámetros son conocidos a priori; el segundo es desarrollar un algoritmo efectivo para la reducción de objetivos facilitando la resolución de problemas multi-objetivo; y finalmente se han implementado una serie de mejoras en el método de la restricción epsilon para mejorar la eficiencia en la resolución de problemas multi-objetivo. Todos los algoritmos presentados han sido comparados y evaluados con los métodos establecidos por la literatura.<br>Optimization has become a major area in process systems engineering. It has evolved from a methodology of academic interest into a technology that has and continues to make significant impact in industry. In this thesis we have focused on development of tools based on two standard optimization methods: mathematical programming and metaheuristics. The objectives of this thesis are: firstly, the development of a hybrid metaheuristic for optimizing the design of supply chains, single objective (cost or benefit), where all parameters are known previously; secondly, the development of an effective algorithm for objective reduction facilitating the resolution of multi-objective problems; and finally, we improved the epsilon-constraint algorithm in multi-objective optimization. All the algorithms presented have been assessed with the methods established in the literature.
6
Sattar, Abdul. "Face analysis by using hybrid single objective and hybrid multiple objective optimizations in 2. 5D active appearance model." Rennes 1, 2010. http://www.theses.fr/2010REN1S021.
Full textAbstract:
L'équipe SCEE de Supélec travaille dans le domaine de la radio logicielle et intelligente, encore appelée Radio Cognitive (CR - Cognitive Radio). Dans cette thèse, nous avons présenté une solution pour l'analyse de visage temps réel dans un équipement de radio cognitive. Dans ce cadre particulier, nous proposons des solutions d'analyse de visage, à savoir «l'estimation de la pose et des caractéristiques faciale d'un visage inconnu orienté ». Nous proposons deux systèmes d'alignement de visages. 1) Le premier exploite un AAM 2. 5D et une seule caméra. La phase d'optimisation de cet AAM est hybride: elle mixe un algorithme génétique et une descente de gradient. Notre contribution tient dans l'opérateur de descente de gradient qui travaille de concert avec l'opérateur classique de mutation : de cette manière sa présence ne pénalise pas la vitesse d'exécution du système. 2) Le second met en œuvre un AAM 2. 5D mais exploite plusieurs caméras. La recherche de la meilleure solution découle également d'une approche hybride qui mixe une optimisation multi-objectifs : le NSGA-II, avec une descente de gradient. Notre contribution tient dans la proposition d'une méthode efficace pour extraire des informations concernant la pertinence de chacune des vues, ces informations sont ensuite exploitées par la descente de gradient. Des comparaisons quantitatives et qualitatives avec d'autres approches mono et multi-objectifs montrent l'intérêt de notre méthode lorsqu'il s'agit d'évaluer la pose et les traits caractéristiques d'un visage inconnu<br>In this study we are interested in the pose estimation and precise localization of face features such as the eyes, the nose and the mouth of an out-of-plane rotated unknown face. Main application of this thesis work is in the Cognitive Radio equipments. We place ourselves within the framework of a low quality acquisition with camera(s) installed on Cognitive Radio equipments e. G. Mobile phone, laptop, desktop computers etc. The face pose and localization of facial features in an unconstrained environment are the major problems for CR equipment. All of its subsequent face related applications (e. G. Face recognition, face synthesis, face data compression etc. ) highly depend upon the methods used for the facial analysis system. In order to extract face features, we use the Active Appearance Models (AAM), deformable models allowing shape and texture to be jointly synthesized. We initially propose a new 2. 5D AAM, based on 3D model, which makes it possible to perform pose estimation and features localization of an oriented face. Secondly, we propose a new optimization methodology for the face search by AAM, in a single camera system, by the hybridization of deterministic and direct search method which has never been used and tested before. Our method hybridizes Gradient Descent (GD) inside the Genetic Algorithm (GA) in a unique way. Along with other operators of GA we propose gradient operator which works in conjunction with the mutation operator of GA thus it does not make the system computationally expensive. Finally for a complete facial analysis system by multiple cameras, we proposed a new concept of multi-objective AAM. In this method, facial images from multiple cameras are analyzed simultaneously by 2. 5D AAM. For the face search optimization we propose a unique way of hybridizing GD with NSGA-II (Non-dominating Search Genetic Algorithm-II). Both of our propositions are robust, real time, efficient and extract facial features even in unknown and out-of-plane rotated faces
7
Amouzgar, Kaveh. "Multi-objective optimization using Genetic Algorithms." Thesis, Högskolan i Jönköping, Tekniska Högskolan, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-19851.
Full textAbstract:
In this thesis, the basic principles and concepts of single and multi-objective Genetic Algorithms (GA) are reviewed. Two algorithms, one for single objective and the other for multi-objective problems, which are believed to be more efficient are described in details. The algorithms are coded with MATLAB and applied on several test functions. The results are compared with the existing solutions in literatures and shows promising results. Obtained pareto-fronts are exactly similar to the true pareto-fronts with a good spread of solution throughout the optimal region. Constraint handling techniques are studied and applied in the two algorithms. Constrained benchmarks are optimized and the outcomes show the ability of algorithm in maintaining solutions in the entire pareto-optimal region. In the end, a hybrid method based on the combination of the two algorithms is introduced and the performance is discussed. It is concluded that no significant strength is observed within the approach and more research is required on this topic. For further investigation on the performance of the proposed techniques, implementation on real-world engineering applications are recommended.
8
Ebadi, Nasim. "Estimating Costs of Reducing Environmental Emissions From a Dairy Farm: Multi-objective epsilon-constraint Optimization Versus Single Objective Constrained Optimization." Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/99304.
Full textAbstract:
Agricultural production is an important source of environmental emissions. While water quality concerns related to animal agriculture have been studied extensively, air quality issues have become an increasing concern. Due to the transfer of nutrients between air, water, and soil, emissions to air can harm water quality. We conduct a multi-objective optimization analysis for a representative dairy farm with two different approaches: nonlinear programming (NLP) and ϵ-constraint optimization to evaluate trade-offs among reduction of multiple pollutants including nitrogen (N), phosphorus (P), greenhouse gas (GHG), and ammonia. We evaluated twenty-six different scenar- ios in which we define incremental reductions of N, P, ammonia, and GHG from five to 25% relative to a baseline scenario. The farm entails crop production, livestock production (dairy and broiler), and manure management activities. Results from NLP optimization indicate that reducing P and ammonia emissions is relatively more expen- sive than N and GHG. This result is also confirmed by the ϵ-constraint optimization. However, the latter approach provides limited evidence of trade-offs among reduction of farm pollutants and net returns, while the former approach includes different re- duction scenarios that make trade-offs more evident. Results from both approaches indicate changes in crop rotation and land retirement are the best strategies to reduce N and P emissions while cow diet changes involving less forage represents the best strategy to reduce ammonia and GHG emissions.<br>Master of Science<br>Human activities often damage and deplete the environment. For instance, nutrient pollution into air and water, which mostly comes from agricultural and industrial activ- ities, results in water quality degradation. Thus, mitigating the detrimental impacts of human activities is an important step toward environmental sustainability. Reducing environmental impacts of nutrient pollution from agriculture is a complicated problem, which needs a comprehensive understanding of types of pollution and their reduction strategies. Reduction strategies need to be both feasible and financially viable. Con- sequently, practices must be carefully selected to allow farmers to maximize their net return while reducing pollution levels to reach a satisfactory level. Thus, this paper conducts a study to evaluate the trade-offs associated with farm net return and re- ducing the most important pollutants generated by agricultural activities. The results of this study show that reducing N and GHG emissions from a representative dairy farm is less costly than reducing P and ammonia emissions, respectively. In addition, reducing one pollutant may result in reduction of other pollutants. In general, for N and P emissions reduction land retirement and varying crop rotations are the most effective strategies. However, for reducing ammonia and GHG emissions focusing on cow diet changes involving less forage is the most effective strategy.
9
Chowdhury, Souma. "Modified predator-prey (MPP) algorithm for single-and multi-objective optimization problems." FIU Digital Commons, 2008. http://digitalcommons.fiu.edu/etd/2352.
Full textAbstract:
The aim of this work is to develop an algorithm that can solve multidisciplinary design optimization problems. In predator-prey algorithm, a relatively small number of predators and a much larger number of prey are randomly placed on a two dimensional lattice with connected ends. The predators are partially or completely biased towards one or more objectives, based on which each predator kills the weakest prey in its neighborhood. A stronger prey created through evolution replaces this prey. In case of constrained problems, the sum o f constraint violations serves as an additional objective.
Modifications of the basic predator-prey algorithm have been implemented in this study regarding the selection procedure, apparent movement of the predators, mutation strategy, dynamics of the Pareto convergence, etc. Further modifications have been made making the algorithm capable of handling equality and inequality constraints. The final modified algorithm is tested on standard constrained/unconstrained, single and multi-objective optimization problems.
10
Bin, Hussin Mohamed Saifullah. "Stochastic local search algorithms for single and bi-objective quadratic assignment problems." Doctoral thesis, Universite Libre de Bruxelles, 2015. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/222286.
Full textAbstract:
The study of Stochastic Local Search (SLS) algorithms is becoming more pivotal these days, due to their vast number of applications in decision making. Prior to the implementation of algorithmic knowledge for decision making, many decisions were made based on manual calculation, on the fly, or even based on guts feeling. Nowadays, such an approach is more rarely seen, especially when the decisions that need to be made are high-risk, cost intensive, or time-consuming. The increasingly often used SLS algorithms are one of the options available to assist the decision making process these days.The work discussed in this thesis concerns the study of SLS algorithms for solving the Quadratic Assignment Problem (QAP), a prominent combinatorial optimization problem, which until today is very hard to solve. Our interest is to study the behavior and performance of SLS algorithms for solving QAP instances of different characteristics, such as size, sparsity, and structure. In this study, we have also proposed new variants of SLS algorithms, inspired by existing, well-performing SLS algorithms for solving the QAP. The new variants of SLS algorithms are then further extended for solving the bi-objective QAP (bQAP).One main focus in this study is to see how the performance of algorithms scales with instance size. We have considered instances that are much larger than the ones usually used in the studies of algorithms for solving the QAP. By understanding how the algorithms perform when the instance size changes, we might be able to solve other problems effectively by considering the similarity in their characteristics to the ones of the QAP, or by seeing common trends in the relative performance of the various available SLS methods. For single objective QAP instances we found that the structure and size of instances do have a significant impact on the performance of SLS algorithms. For example, comparisons between Tabu Search (TS) and Simulated Annealing (SA) on instances with randomly generated matrices show that the overall performance of TS is better than SA, irrespective the size of instances considered. The results on a class of structured instances however show that TS performs well on small-sized instances, while on the larger ones, SA shows better results. In another experiment, Hierarchical Iterated Local Search (HILS) has shown very good results compared to several Iterated Local Search (ILS) variants. This experiment was done on a class of structured instances of size from 100 to 500. An extensive experiment on a class of structured instances of size 30 to 300 using tuned parameter settings shows that population based algorithms perform very well on most of the instance classes considered. SA however, shows very good performance especially on large-sized instances with low sparsity level. For the bQAP, the correlation between the flow matrices does have a strong effect that determines the performance of algorithms for solving them. Hybrid Simulated Annealing (HSA) clearly outperforms Hybrid Iterative Improvement (HII). When compared to Multi Objective Ant Colony Optimization (MOACO) and Strength Pareto Evolutionary Algorithm 2 (SPEA2), HSA shows very good performance, where HSA outperforms MOACO and SPEA2, especially on instances of large size, thus, offering a better scaling behavior. Based the results obtained in this study, it is possible to come up with a general idea on the suitability of SLS algorithms for solving instances with a certain characteristic. Given an unknown QAP instance, one can guess the most suitable algorithm for solving it depending on the type, size, and sparsity of the instance, while for a bQAP instance the most suitable algorithm can be guessed based on its size and correlation between the flow matrices.<br>Doctorat en Sciences de l'ingénieur et technologie<br>info:eu-repo/semantics/nonPublished
11
Morcos, Karim M. "Genetic network parameter estimation using single and multi-objective particle swarm optimization." Thesis, Kansas State University, 2011. http://hdl.handle.net/2097/9207.
Full textAbstract:
Master of Science<br>Department of Electrical and Computer Engineering<br>Sanjoy Das<br>Stephen M. Welch<br>Multi-objective optimization problems deal with finding a set of candidate optimal solutions to be presented to the decision maker. In industry, this could be the problem of finding alternative car designs given the usually conflicting objectives of performance, safety, environmental friendliness, ease of maintenance, price among others. Despite the significance of this problem, most of the non-evolutionary algorithms which are widely used cannot find a set of diverse and nearly optimal solutions due to the huge size of the search space. At the same time, the solution set produced by most of the currently used evolutionary algorithms lacks diversity.
The present study investigates a new optimization method to solve multi-objective problems based on the widely used swarm-intelligence approach, Particle Swarm Optimization (PSO). Compared to other approaches, the proposed algorithm converges relatively fast while maintaining a diverse set of solutions. The investigated algorithm, Partially Informed Fuzzy-Dominance (PIFD) based PSO uses a dynamic network topology and fuzzy dominance to guide the swarm of dominated solutions.
The proposed algorithm in this study has been tested on four benchmark problems and other real-world applications to ensure proper functionality and assess overall performance. The multi-objective gene regulatory network (GRN) problem entails the minimization of the coefficient of variation of modified photothermal units (MPTUs) across multiple sites along with the total sum of similarity background between ecotypes. The results throughout the current research study show that the investigated algorithm attains outstanding performance regarding optimization aspects, and exhibits rapid convergence and diversity.
12
Beirigo, Breno Alves. "Single-objective and bi-objetive parallel heuristics for the travel planning problem." Universidade Federal de Viçosa, 2016. http://www.locus.ufv.br/handle/123456789/9489.
Full textAbstract:
Submitted by Reginaldo Soares de Freitas (reginaldo.freitas@ufv.br) on 2017-02-10T15:29:30Z
No. of bitstreams: 1
texto completo.pdf: 2736980 bytes, checksum: f41dd8d979519bbcc7b9d7350c591432 (MD5)<br>Made available in DSpace on 2017-02-10T15:29:30Z (GMT). No. of bitstreams: 1
texto completo.pdf: 2736980 bytes, checksum: f41dd8d979519bbcc7b9d7350c591432 (MD5)
Previous issue date: 2016-09-21<br>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior<br>In this study we apply single-objective and bi-objective parallel heuristics to solve broad and realistic formulations of the travel planning problem. Given a travel time window and a set of destinations with their corresponding dwelling times, the goal of our single-objective approach is to find a route that produces a budget travel’s itinerary, involving flights, hotels and departure/arrival times. In turn, our bi-objective approach adds a complexity level in the problem’s formulation once we are seeking for a Pareto set of detailed travel itineraries, which are both cost and time efficient. When the sequence of cities is fixed, the single-objective version of the problem is commonly modeled in literature as a time-dependent network and the best itinerary is computed using shortest path algorithms. However, in this study, finding the order of cities that minimizes the total cost, and besides that, a set of good trade-off solutions, are also goals. Therefore, our single-objective formulation stands for a TDSPP (Time Dependent Shortest Path Problem) embedded in the TSP (Travel Salesman Problem) whereas our bi-objective formulation stands for a TDSPP embedded in a bi-objective TSP. On the first formulation we apply an ILS (Iterated Local Search) heuristic and on the second formulation we apply the NSGA-II (Nondominated Sorting Genetic Algorithm II) framework. For performance assessing, the results of both heuristics were compared to the results of corresponding exact methods with no time constraints. All test cases simulate realistic travel itineraries and run upon real-world travel data collected in advance, besides having to comply with an execution threshold of approximately 1 minute. For 285 single-objective test cases, our ILS heuristic was able to reach solutions in average less than 4.1% divergent from an exact implementation, besides reaching the optimal solution in about 30% of the test cases. In turn, for 180 bi-objective test cases, our NSGA-II implementation was able to reach an approximated solution in average up to 8% divergent from an exact implementation.<br>Nesse trabalho são aplicadas heurísticas paralelas mono-objetivas e bi-objetivas para solucionar formulações abrangentes e realistas do problema de planejamento de viagens. Dado o intervalo de tempo que uma viagem pode ocorrer e um conjunto de destinos com seus respectivos tempos de permanência, a abordagem mono-objetiva procura determinar um itinerário de baixo custo que compreenda voos, hotéis e horários de partida/chegada. Por sua vez, a abordagem bi-objetiva adiciona complexidade a formulação do problema, uma vez que pretende determinar o conjunto Pareto de itinerários de viagem capazes de equilibrar custo e tempo. Quando a sequência de cidades é fixa, a versão mono-objetiva do problema é comumente modelada na literatura como uma rede dependente do tempo e o melhor itinerário é calculado usando algoritmos de caminho míınimo. Contudo, nesse trabalho, determinar a ordem de visitação das cidades também é um objetivo. Portanto, a formulação mono-objetiva proposta representa um TDSPP (Time Dependent Shortest Path Problem) incorporado ao TSP (Travel Salesman Problem) e a formulação bi-objetiva representa um TDSPP incorporado em um TSP bi-objetivo. Na primeira formulação foi aplicada a heurística ILS (Iterated Local Search) e na segunda formulação o framework NSGA-II (Nondominated Sorting Genetic Algorithm II). Os resultados de ambas as heurísticas foram comparados com os resultados produzidos por métodos exatos executados sem restrições temporais. Todos os casos de teste simulam itinerários de viagem realistas e foram executados em um banco de dados de viagens e hospedagens coletadas com antecedência. Além disso, independentemente da abordagem utilizada, estabeleceu-se que o tempo de execução de cada caso deve ser de aproximadamente 1 minuto. A heurística ILS proposta para a versão mono-objetiva do problema foi executada em 285 instâncias e alcançou, em média, soluçõoes no máximo 4.1% divergentes de uma implementa ̧ao exata, além de atingir a melhor solução em cerca de 30% dos casos de teste. Por sua vez, o framework NSGA-II foi capaz de produzir soluções no máximo 8% divergentes da implementação exata para 180 instâncias.
13
Latiff, Idris Abd. "Global-adaptive particle swarm optimisation algorithms for single and multi-objective optimisation problems." Thesis, University of Sheffield, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.548633.
Full text
14
Krumpe, Norman Joseph. "A COMPARISON OF SIMULATION OPTIMIZATION TECHNIQUES IN SOLVING SINGLE-OBJECTIVE, CONSTRAINED, DISCRETE VARIABLE PROBLEMS." Miami University / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=miami1129749397.
Full text
15
Li, Mian. "Robust optimization and sensitivity analysis with multi-objective genetic algorithms single- and multi-disciplinary applications /." College Park, Md.: University of Maryland, 2007. http://hdl.handle.net/1903/7672.
Full textAbstract:
Thesis (Ph. D.) -- University of Maryland, College Park, 2007.<br>Thesis research directed by: Dept. of Mechanical Engineering. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
16
Leclerc, Marc-Antoine François. "The effects of single-objective management on disturbances in central interior dry forests of British Columbia." Thesis, University of British Columbia, 2017. http://hdl.handle.net/2429/62778.
Full textAbstract:
Mule deer are an important game species, and have become the focus of applying a particular silvicultural treatment that enhances habitat while allowing timber harvesting. Mule deer winter range management (MDWRM) involves the proportional removal of trees based on their diameter and abundance resulting in a multilayered, Douglas-fir dominated forest with a clumpy tree distribution. I assessed changes in forest stand attributes brought about by MDWRM through time and how these attributes related to stand susceptibility to the western spruce budworm, Douglas-fir beetle, and wildfire using a randomized complete block single factor mixed-effects model with subsampling. In the short-term, MDWRM significantly changed (p<0.05) forest stand attributes by decreasing sub-canopy tree density and basal area, canopy cover, leaf area index, and increasing large surface fuel load. In the long-term, most attributes recovered to untreated levels. Relative to untreated stands, treated stands maintained a multilayered structure and an abundance of Douglas-fir trees thus their susceptibility to the western spruce budworm did not change through time. In the short-term, a reduction in mature host-tree density lowered susceptibility to the Douglas-fir beetle. With subsequent forest recovery, long-term susceptibility did not differ relative to untreated stands. In the treated stands the likelihood of crown fire was greater shortly after than longer after treatment. This was likely due to more large surface fuels immediately following treatment. In addition, I extrapolated the effects of MDWRM across eligible stands of interior British Columbia in a hypothetical simulation to evaluate the current and forecasted landscape-level fire risk. The forecasted forest under widespread application of MDWRM resulted in a homogenized landscape dominated by low fire risk. Further, widespread application of MDWRM may result in a fire resilient landscape, but with consequences for other ecological processes. The present study contributes to our understanding of the relationship between single-objective management and subsequent stand susceptibility to biotic and abiotic disturbances. I concluded that understanding this relationship should play an important role in responsible resource management.<br>Forestry, Faculty of<br>Graduate
17
Allard, David M. "A Multi-Objective Genetic Algorithm to Solve Single Machine Scheduling Problems Using a Fuzzy Fitness Function." Ohio University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1180968613.
Full text
18
Maußner, Johannes [Verfasser], Hannsjörg [Akademischer Betreuer] Freund, and Hannsjörg [Gutachter] Freund. "Single- and Multi-Objective Reactor Design Under Uncertainty / Johannes Maußner ; Gutachter: Hannsjörg Freund ; Betreuer: Hannsjörg Freund." Erlangen : Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 2020. http://d-nb.info/1217065156/34.
Full text
19
Besharati, Babak. "Deterministic multi-objective robust optimization for single product and product line engineering with design and marketing considerations." College Park, Md. : University of Maryland, 2006. http://hdl.handle.net/1903/3522.
Full textAbstract:
Thesis (Ph. D.) -- University of Maryland, College Park, 2006.<br>Thesis research directed by: Mechanical Engineering. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
20
Liogys, Mindaugas. "Darbų grafikų sveikatos priežiūros įstaigose optimizavimas." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2013. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2013~D_20130930_092424-50923.
Full textAbstract:
Šioje disertacijoje nagrinėjamas sveikatos priežiūros įstaigos darbuotojų darbų grafikų optimizavimo uždavinys, kuris formuluojamas ir sprendžiamas, remiantis vienos didžiausių Lietuvos sveikatos priežiūros įstaigų, realiais duomenimis. Disertacijoje apžvelgiami darbų grafikų optimizavimo uždaviniai bei jų sprendimo metodai, atlikta naujausių šaltinių, tiriančių panašius uždavinius, analizė. Antrame skyriuje nagrinėjamasis darbų grafikų optimizavimo uždavinys suformuluotas matematiškai. Pateikiamos dvi formuluotės: vienakriterio ir daugiakriterio optimizavimo uždavinio. Aprašomos sąlygos, kurias turi tenkinti sudaromasis darbų grafikas. Trečiajame skyriuje nagrinėjami metodai, tiek vienakriteriams, tiek daugiakriteriams uždaviniams spręsti. Pasiūlytas naujas metodas, kuris efektyviau nei kiti nagrinėti metodai sprendžia šioje disertacijoje suformuluotą uždavinį. Ketvirtame skyriuje pateikiami pasiūlyto metodo eksperimentinio tyrimo rezultatai. Pirmoje skyriaus dalyje analizuojami rezultatai gauti, sprendžiant vienakriterį optimizavimo uždavinį, o antroje dalyje – daugiakriterį optimizavimo uždavinį. Disertacijos tyrimų rezultatai buvo pristatyti respublikinėje konferencijoje ir trijose tarptautinėse konferencijose bei publikuoti trijuose mokslo žurnaluose.<br>In this dissertation nurse rostering problem is investigated. The formulation of the problem is based on real-world data of one of the largest healthcare centers in Lithuania. Most recent publications that tackle the nurse rostering problem and the methods for solving the nurse rostering problem are reviewed in this dissertation. The mathematical formulation of the single objective and the multi-objective nurse rostering problem is presented and the requirements for the roster are described in the second chapter. In the third chapter, the methods for solving the single objective and the multi-objective nurse rostering problem are described. A new method for solving the single objective and the multi-objective nurse rostering problem is proposed in the third chapter. In the fourth chapter, the experimental results of our proposed method are introduced. In the first section of this chapter, the results gathered solving single-objective optimization problem are analyzed, and in the second section of this chapter, the results gathered solving multi-objective optimization problem are analyzed. Dissertation research results were presented at one national conference and three international conferences and published in three scientific journals.
21
Pennada, Venkata Sai Teja. "Solving Multiple Objective Optimization Problem using Multi-Agent Systems: A case in Logistics Management." Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-20745.
Full textAbstract:
Background: Multiple Objective Optimization problems(MOOPs) are common and evident in every field. Container port terminals are one of the fields in which MOOP occurs. In this research, we have taken a case in logistics management and modelled Multi-agent systems to solve the MOOP using Non-dominated Sorting Genetic Algorithm-II (NSGA-II). Objectives: The purpose of this study is to build AI-based models for solving a Multiple Objective Optimization Problem occurred in port terminals. At first, we develop a port agent with an objective function of maximizing throughput and a customer agent with an objective function of maximizing business profit. Then, we solve the problem using the single-objective optimization model and multi-objective optimization model. We then compare the results of both models to assess their performance. Methods: A literature review is conducted to choose the best algorithm among the existing algorithms, which were used previously in solving other Multiple Objective Optimization problems. An experiment is conducted to know how well the models performed to solve the problem so that all the participants are benefited simultaneously. Results: The results show that all three participants that are port, customer one and customer two have gained profits by solving the problem in multi-objective optimization model. Whereas in a single-objective optimization model, a single participant has achieved earnings at a time, leaving the rest of the participants either in loss or with minimal profits. Conclusion: We can conclude that multi-objective optimization model has performed better than the single-objective optimization model because of the impartial results among the participants.
22
Ferruzza, Davide. "Thermocline storage for concentrated solar power : Techno-economic performance evaluation of a multi-layered single tank storage for Solar Tower Power Plant." Thesis, KTH, Kraft- och värmeteknologi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-172456.
Full textAbstract:
Solar Tower Power Plants with thermal energy storage are a promising technology for dispatchable renewable energy in the near future. Storage integration makes possible to shift the electricity production to more profitable peak hours. Usually two tanks are used to store cold and hot fluids, but this means both higher related investment costs and difficulties during the operation of the variable volume tanks. Another solution can be a single tank thermocline storage in a multi-layered configuration. In such tank both latent and sensible fillers are employed to decrease the related cost by up to 30% and maintain high efficiencies. The Master thesis hereby presented describes the modelling and implementation of a thermocline-like multi-layered single tank storage in a STPP. The research work presents a comprehensive methodology to determine under which market structures such devices can outperform the more conventional two tank storage systems. As a first step the single tank is modelled by means of differential energy conservation equations. Secondly the tank geometrical design parameters and materials are taken accordingly with the applications taken into consideration. Both the steady state and dynamic models have been implemented in an existing techno-economic tool developed in KTH, in the CSP division (DYESOPT). The results show that under current cost estimates and technical limitations the multi-layered solid PCM storage concept is a better solution when peaking operating strategies are desired, as it is the case for the two-tier South African tariff scheme. In this case the IRR of an optimal designed power plant can be decreased by 2.1%. However, if a continuous operation is considered, the technology is not always preferred over the two tank solution, yet is a cheaper alternative with optimized power plants. As a result the obtained LCOE can be decreased by 2.4%.
23
Abu, Bakar Ilyani Akmar Verfasser], and Timon [Akademischer Betreuer] [Rabczuk. "Computational Analysis of Woven Fabric Composites: Single- and Multi-Objective Optimizations and Sensitivity Analysis in Meso-scale Structures / Ilyani Akmar Abu Bakar ; Betreuer: Timon Rabczuk." Weimar : Bauhaus-Universität Weimar, 2020. http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200605-41762.
Full text
24
Abu, Bakar Ilyani Akmar [Verfasser], and Timon [Akademischer Betreuer] Rabczuk. "Computational Analysis of Woven Fabric Composites: Single- and Multi-Objective Optimizations and Sensitivity Analysis in Meso-scale Structures / Ilyani Akmar Abu Bakar ; Betreuer: Timon Rabczuk." Weimar : Bauhaus-Universität Weimar, 2020. http://d-nb.info/1211959422/34.
Full text
25
Albandes, Iuri. "Use of Approximate Triple Modular Redundancy for Fault Tolerance in Digital Circuits." Doctoral thesis, Universidad de Alicante, 2018. http://hdl.handle.net/10045/88248.
Full textAbstract:
La triple redundancia modular (TMR) es una técnica bien conocida de mitigación de fallos que proporciona una alta protección frente a fallos únicos pero con un gran coste en términos de área y consumo de potencia. Por esta razón, la redundancia parcial se suele aplicar para aligerar estos sobrecostes. En este contexto, la TMR aproximada (ATMR), que consisten en la implementación de la redundancia triple con versiones aproximadas del circuito a proteger, ha surgido en los últimos años como una alternativa a la replicación parcial, con la ventaja de obtener mejores soluciones de compromiso entre la cobertura a fallos y los sobrecostes. En la literatura ya han sido propuestas varias técnicas para la generación de circuitos aproximados, cada una con sus pros y sus contras. Este trabajo realiza un estudio de la técnica ATMR, evaluando el coste-beneficio entre el incremento de recursos (área) y la cobertura frente a fallos. La primera contribución es una nueva aproximación ATMR donde todos los módulos redundantes son versiones aproximadas del diseño original, permitiendo la generación de circuitos ATMR con un sobrecoste de área muy reducido, esta técnica se denomina Full-ATMR (ATMR completo o FATMR). El trabajo también presenta una segunda aproximación para implementar la ATMR de forma automática combinando una biblioteca de puertas aproximadas (ApxLib) y un algoritmo genético multi-objetivo (MOOGA). El algoritmo realiza una búsqueda ciega sobre el inmenso espacio de soluciones, optimizando conjuntamente la cobertura frente a fallos y el sobrecoste de área. Los experimentos comparando nuestra aproximación con las técnicas del estado del arte muestran una mejora de los trade-offs para diferentes circuitos de prueba (benchmark).
26
Tiene, Sara. "Genetic algorithms for construction management: the case study of a building envelope design optimization." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017.
Find full textAbstract:
The present work deals with the study and analysis of the simultaneous optimization of time, cost and quality by using artificial intelligence technique; The approach is based on the use of genetic algorithms implemented in Matlab applied to a case study, the construction of a new University Campus in Cesena, focusing on the external walls of the building itself. The objective is to find a set of optimal solutions, equally valid, for the realization of stratigraphies of the different types of external masonry; It will then be the task of the designer to choose among possible solutions which he believes to be most appropriate, based on the requirements of the project, which may be in terms of quality, cost, time or a combination of two or more of these evaluation parameters. It will thus illustrate how different solutions provided by the program can be used and collected in a three-dimensional graph.
27
Jesus, Luiz Henrique Reis de. "Aplicação interativa em processos de otimização por método das estratégias de evolução." Universidade Federal de Goiás, 2017. http://repositorio.bc.ufg.br/tede/handle/tede/7458.
Full textAbstract:
Submitted by Luciana Ferreira (lucgeral@gmail.com) on 2017-06-14T11:09:20Z
No. of bitstreams: 2
license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)
Dissertação - Luiz Henrique Reis de Jesus - 2017.pdf: 3311759 bytes, checksum: 20e4044376c2666f102131892f7b3fc2 (MD5)<br>Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2017-06-14T11:09:35Z (GMT) No. of bitstreams: 2
license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)
Dissertação - Luiz Henrique Reis de Jesus - 2017.pdf: 3311759 bytes, checksum: 20e4044376c2666f102131892f7b3fc2 (MD5)<br>Made available in DSpace on 2017-06-14T11:09:35Z (GMT). No. of bitstreams: 2
license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)
Dissertação - Luiz Henrique Reis de Jesus - 2017.pdf: 3311759 bytes, checksum: 20e4044376c2666f102131892f7b3fc2 (MD5)
Previous issue date: 2017-05-15<br>Conselho Nacional de Pesquisa e Desenvolvimento Científico e Tecnológico - CNPq<br>This dissertation of master degree describes an approach of the interactive optimization process
associate to the Evolution Strategies method for the evaluation of the loudspeaker optimization
project, with the objective to present the advantages achieved after the user interventions
throughout the optimization process. Its development is based on the methodology of the Evolution
Strategies characterized by the concept of natural selection, which uses combination and mutation
methods to generate new individuals. However, for greater efficiency in the responses of the
objective function, as well as the reduction in its convergence time, the optimization process
requires interventions in stabilization of local minima and maxima. In the interventions made
available to the user, will be considered manipulations in the operators of mutation and
combination, mutation of the parameters of self-adaptation, as well as the change of objective and
the variation of their respective restriction. As a differential, an interface was developed to make
feasible the user interventions applied to the optimization process, as well as the monitoring of the
entire process. In this work, also evaluated optimization test functions with the objective of
validating the proposed methodology.<br>Esta dissertação de mestrado descreve uma abordagem do processo de otimização interativa
associado ao método das Estratégias de Evolução para a avaliação do projeto de otimização do
alto-falante, com o objetivo de apresentar as vantagens alcançadas após as intervenções do usuário
ao longo do processo de otimização. Seu desenvolvimento é baseado na metodologia das
Estratégias de Evolução caracterizada pelo conceito de seleção natural, o qual utiliza de métodos
de combinação e mutação para a geração de novos indivíduos. No entanto, para maior eficiência
nas respostas a função objetivo, bem como a redução em seu tempo de convergência, o processo de
otimização necessita de intervenções em estabilizações de mínimos e máximos locais. Nas
intervenções disponibilizadas ao usuário, serão consideradas manipulações nos operadores de
mutação e combinação, mutação dos parâmetros de auto-adaptação, bem como a mudança de
objetivo e a variação de sua respectiva restrição. Como diferencial, foi desenvolvida uma interface
para viabilizar as intervenções do usuário aplicadas ao processo de otimização, bem como o
acompanhamento de todo o processo. Neste trabalho, também foram avaliadas funções de teste de
otimização com o objetivo de validar a metodologia proposta.
28
Mundt, Andreas, and Thomas Wich. "Single Machine Scheduling with Tardiness Involved Objectives : A Survey." Thesis, Linköping University, Department of Mathematics, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8628.
Full textAbstract:
<p>This thesis contributes to theoretical and quantitative aspects of machine scheduling. In fact, it is dedicated to the issue of scheduling n jobs on one single machine. The scope is limited to deterministic problems - i.e. those with all data available and known with certainty in advance - with tardiness involved objectives; hence, the common denominator of all problems addressed are jobs with a predetermined due date assigned to. A job is finished on time as long as it is completed before its due date, otherwise it is said to be tardy. Since the single machine utilized is assumed to be restricted to process at most one job at a time, the aim is to find a proper sequence - a schedule - of how to process the jobs in order to best fulfill a certain objective. The contribution of this thesis aims at giving a state of the art survey and detailed review of research effort considering the objectives "minimizing the number of tardy jobs" and "minimizing the weighted number of tardy jobs". Further, the objectives of "minimizing the total tardiness", "minimizing the total weighted tardiness" and "minimizing the maximum tardiness" are adumbrated but reduced to a rough overview of research effort made.</p>
29
Oujebbour, Fatima Zahra. "Méthodes et applications industrielles en optimisation multi-critère de paramètres de processus et de forme en emboutissage." Phd thesis, Université Nice Sophia Antipolis, 2014. http://tel.archives-ouvertes.fr/tel-00976639.
Full textAbstract:
Face aux exigences concurrentielles et économiques actuelles dans le secteur automobile, l'emboutissage a l'avantage, comme étant un procédé de mise en forme par grande déformation, de produire, en grandes cadences, des pièces de meilleure qualité géométrique par rapport aux autres procédés de fabrication mécanique. Cependant, il présente des difficultés de mise en œuvre, cette dernière s'effectue généralement dans les entreprises par la méthode classique d'essai-erreur, une méthode longue et très coûteuse. Dans la recherche, le recours à la simulation du procédé par la méthode des éléments finis est une alternative. Elle est actuellement une des innovations technologiques qui cherche à réduire le coût de production et de réalisation des outillages et facilite l'analyse et la résolution des problèmes liés au procédé. Dans le cadre de cette thèse, l'objectif est de prédire et de prévenir, particulièrement, le retour élastique et la rupture. Ces deux problèmes sont les plus répandus en emboutissage et présentent une difficulté en optimisation puisqu'ils sont antagonistes. Une pièce mise en forme par emboutissage à l'aide d'un poinçon sous forme de croix a fait l'objet de l'étude. Nous avons envisagé, d'abord, d'analyser la sensibilité des deux phénomènes concernés par rapport à deux paramètres caractéristiques du procédé d'emboutissage (l'épaisseur du flan initial et de la vitesse du poinçon), puis par rapport à quatre (l'épaisseur du flan initial, de la vitesse du poinçon, l'effort du serre flan et le coefficient du frottement) et finalement par rapport à la forme du contour du flan. Le recours à des méta-modèles pour optimiser les deux critères était nécessaire.
30
Xie, Wenbin. "Metaheuristics for single and multiple objectives production scheduling for the capital goods industry." Thesis, University of Newcastle Upon Tyne, 2011. http://hdl.handle.net/10443/1261.
Full textAbstract:
In the capital goods industry, companies produce plant and machinery that is used to produce consumer products or commodities such as electricity or gas. Typical products produced in these companies include steam turbines, large boilers and oil rigs. Scheduling of these products is difficult due to the complexity of the product structure, which involves many levels of assembly and long complex routings of many operations which are operated in multiple machines. There are also many scheduling constraints such as machine capacity as well as operation and assembly precedence relationships. Products manufactured in the capital goods industry are usually highly customised in order to meet specific customer requirements. Delivery performance is a particularly important aspect of customer service and it is common for contracts to include severe penalties for late deliveries. Holding costs are incurred if items are completed before the due date. Effective planning and inventory control are important to ensure that products are delivered on time and that inventory costs are minimised. Capital goods companies also give priority to resource utilisation to ensure production efficiency. In practice there are tradeoffs between achieving on time delivery, minimising inventory costs whilst simultaneously maximising resource utilisation. Most production scheduling research has focused on job-shops or flow-shops which ignored assembly relationships. There is a limited literature that has focused on assembly production. However, production scheduling in capital goods industry is a combination of component manufacturing (using jobbing, batch and flow processes), assembly and construction. Some components have complex operations and routings. The product structures for major products are usually complex and deep. A practical scheduling tool not only needs to solve some extremely large scheduling problems, but also needs to solve these problems within a realistic time. Multiple objectives are usually encountered in production scheduling in the capital goods industry. Most literature has focused on minimisation of total flow time, or makespan and earliness and tardiness of jobs. In the capital goods industry, inventory costs, delivery performance and machine utilisation are crucial competitive. This research develops a scheduling tool that can successfully optimise these criteria simultaneously within a realistic time. ii The aim of this research was firstly to develop the Enhanced Single-Objective Genetic Algorithm Scheduling Tool (ESOGAST) to make it suitable for solving very large production scheduling problems in capital goods industry within a realistic time. This tool aimed to minimise the combination of earliness and lateness penalties caused by early or late completion of items. The tool was compared with previous approaches in literature and was proved superior in terms of the solution quality and the computational time. Secondly, this research developed a Multi-Objective Genetic Algorithm Scheduling Tool (MOGAST) that was based upon the development of ESOGAST but was able to solve scheduling problems with multiple objectives. The objectives of this tool were to optimise delivery performance, minimise inventory costs, and maximise resource utilisation simultaneously. Thirdly, this research developed an Artificial Immune System Scheduling Tool (AISST) that achieved the same objective of the ESOGAST. The performances of both tools were compared and analysed. Results showed that AISST performs better than ESOGAST on relatively small scheduling problems, but the computation time required by the AISST was several times longer. However ESOGAST performed better than the AISST for larger problems. Optimum configurations were identified in a series of experiments that conducted for each tool. The most efficient configuration was also successfully applied for each tool to solve the full size problem and all three tools achieved satisfactory results.
31
Honců, Martina. "Globální granty v neziskovém sektoru." Master's thesis, Vysoká škola ekonomická v Praze, 2008. http://www.nusl.cz/ntk/nusl-4539.
Full textAbstract:
The degree thesis treats the problem of Global grant in nonprofit sector accorded within Single programming document for Objective 3 of the NUTS 2 Prague region. The Global grant is simplified grant scheme awarded to nonprofit organizations active in social sphere, which focus on persons endangered by social exclusion. The degree thesis defines the theoretical framework of all correlations necessary for valid insight into the problem. Among the concepts defined are nonprofit sector, nonprofit organizations, their financing, regional policy of European Union acting through the European Social Fund awarding funds precisely for Global grant. The nature of Global grant is further examined by looking into project approval procedure falling within the grant, handling of monitoring indicators and positron and impact of the Global grant on nonprofit organizations.
32
Marinus, Benoît. "Multidisciplinary optimization of aircraft propeller blades." Phd thesis, Ecole Centrale de Lyon, 2011. http://tel.archives-ouvertes.fr/tel-00692363.
Full textAbstract:
Open rotors are known to have significant advantages in terms of propulsive efficiency. These advantages translate directly in reduced fuel burn so that they nowadays benefit from a surge of interest. At the same time, recent advances in numerical simulations make the application of multidisciplinary optimization for the demanding design of transonic propeller blades, an affordable option. Therefore, an optimization method in which the performance objectives of aerodynamics, aeroacoustics and aeroelasticity compete against each other, is developed and applied for the design of high-speed single-rotation propellers. The optimization is based on Multi-Objective Differential Evolution (MODE).This technique is a particular kind of evolutionary algorithm that mimics the natural evolution of populations by relying on the selection, recombination and eventually mutation of blade designs, each of them being represented by a vector of design variables (e.g. chord width, tip sweep, etc). MODE has the advantage of dealing concurrently with all the objectives in the selection of potentially promising designs among a population. In order to keep the computational cost within reasonable margins, the assessment of the performance of proposed designs is done in a two-level approach. A metamodel provides performance estimates for each proposed design at extremely low computational effort while high-fidelity analysis codes provide accurate performance values on some promising designs at much higher cost. To safeguard the accuracy of the estimates, the metamodel is initially trained on a population that is specifically assembled for that purpose. The training is repeated from time to time with the high-fidelity performance values of promising designs. Different high-fidelity tools have been developed and used for the assessment of performance.The CFD-tool performs steady RANS simulations of a single blade passage of the isolated propeller in free air under zero angle of attack. These simulations provide the aerodynamic performance values. The full propeller is modelled thanks to cyclic boundary conditions. The k - ε turbulence model is used in combination with wall treatment. Adiabatic no-slip wall conditions are imposed on the spinner and blade surfaces whereas the test-section radial boundary is reproducing the effects of a pressure far-field. This approach has proven its robustness and, above all, its accuracy as satisfactory agreement with experimental results has been found for different operating conditions over a wide range of blade shapes, as well as sufficient grid independency. In the post-processing of the aerodynamic results, the Sound Pressure Level (SPL)is computed for tonal noise at various observer locations by the aeroacoustic solver(CHA). Formulation 1A from Farassat is used for this purpose. This formulation is related to the inhomogeneous wave equation derived from Lighthill's acoustic analogy by Ffowcs Williams and Hawkings (FW-H). It benefits from the partial decoupling of the acoustic and aerodynamic aspects and is particularly suited to compute the noise from propellers. The thickness noise and loading noise are expressed by separate equations in the time-domain whereas the quadrupole source term is dropped from the original FW-H equation. The blade surface is chosen as integration surface and a newly developed truncation technique is applied to circumvent the mathematical singularity arising when parts of the blade reach sonic conditions in terms of kinematics with respect to the observer. This approach delivers accurate values at acceptable computational cost. Besides, CSM-computations make use of a finite elements solver to compute the total mass of the blade as well as the stresses resulting from the centrifugal and aerodynamic forces. Considering the numerous possibilities to tailor the blade structure so that it properly takes on the stresses, only a simplified blade model is implemented. [...]
33
Lee, Chee Sing. "Simultaneous localization and mapping using single cluster probability hypothesis density filters." Doctoral thesis, Universitat de Girona, 2015. http://hdl.handle.net/10803/323637.
Full textAbstract:
The majority of research in feature-based SLAM builds on the legacy of foundational work using the EKF, a single-object estimation technique. Because feature-based SLAM is an inherently multi-object problem, this has led to a number of suboptimalities in popular solutions. We develop an algorithm using the SC-PHD filter, a multi-object estimator modeled on cluster processes. This algorithm hosts capabilities not typically seen with feature-base SLAM solutions such as principled handling of clutter measurements and missed detections, and navigation with a mixture of stationary and moving landmarks. We present experiments with the SC-PHD SLAM algorithm on both synthetic and real datasets using an autonomous underwater vehicle. We compare our method to the RB-PHD SLAM, showing that it requires fewer approximations in its derivation and thus achieves superior performance.<br>En aquesta tesis es desenvolupa aquest algoritme a partir d’un filtre PHD amb un únic grup (SC-PHD), una tècnica d’estimació multi-objecte basat en processos d’agrupació. Aquest algoritme té unes capacitats que normalment no es veuen en els algoritmes de SLAM basats en característiques, ja que és capaç de tractar falses característiques, així com característiques no detectades pels sensors del vehicle, a més de navegar en un entorn amb la presència de característiques estàtiques i característiques en moviment de forma simultània. Es presenten els resultats experimentals de l’algoritme SC-PHD en entorns reals i simulats utilitzant un vehicle autònom submarí. Els resultats són comparats amb l’algoritme de SLAM Rao-Blackwellized PHD (RB-PHD), demostrant que es requereixen menys aproximacions en la seva derivació i en conseqüència s’obté un rendiment superior.
34
Teng, Sin Yong. "Intelligent Energy-Savings and Process Improvement Strategies in Energy-Intensive Industries." Doctoral thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2020. http://www.nusl.cz/ntk/nusl-433427.
Full textAbstract:
S tím, jak se neustále vyvíjejí nové technologie pro energeticky náročná průmyslová odvětví, stávající zařízení postupně zaostávají v efektivitě a produktivitě. Tvrdá konkurence na trhu a legislativa v oblasti životního prostředí nutí tato tradiční zařízení k ukončení provozu a k odstavení. Zlepšování procesu a projekty modernizace jsou zásadní v udržování provozních výkonů těchto zařízení. Současné přístupy pro zlepšování procesů jsou hlavně: integrace procesů, optimalizace procesů a intenzifikace procesů. Obecně se v těchto oblastech využívá matematické optimalizace, zkušeností řešitele a provozní heuristiky. Tyto přístupy slouží jako základ pro zlepšování procesů. Avšak, jejich výkon lze dále zlepšit pomocí moderní výpočtové inteligence. Účelem této práce je tudíž aplikace pokročilých technik umělé inteligence a strojového učení za účelem zlepšování procesů v energeticky náročných průmyslových procesech. V této práci je využit přístup, který řeší tento problém simulací průmyslových systémů a přispívá následujícím: (i)Aplikace techniky strojového učení, která zahrnuje jednorázové učení a neuro-evoluci pro modelování a optimalizaci jednotlivých jednotek na základě dat. (ii) Aplikace redukce dimenze (např. Analýza hlavních komponent, autoendkodér) pro vícekriteriální optimalizaci procesu s více jednotkami. (iii) Návrh nového nástroje pro analýzu problematických částí systému za účelem jejich odstranění (bottleneck tree analysis – BOTA). Bylo také navrženo rozšíření nástroje, které umožňuje řešit vícerozměrné problémy pomocí přístupu založeného na datech. (iv) Prokázání účinnosti simulací Monte-Carlo, neuronové sítě a rozhodovacích stromů pro rozhodování při integraci nové technologie procesu do stávajících procesů. (v) Porovnání techniky HTM (Hierarchical Temporal Memory) a duální optimalizace s několika prediktivními nástroji pro podporu managementu provozu v reálném čase. (vi) Implementace umělé neuronové sítě v rámci rozhraní pro konvenční procesní graf (P-graf). (vii) Zdůraznění budoucnosti umělé inteligence a procesního inženýrství v biosystémech prostřednictvím komerčně založeného paradigmatu multi-omics.
35
Change, Chin Ju, and 張欽智. "Solving Single-objective and Multi-objective Traveling Salesman Problem by Tabu Search." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/20516457183892725447.
Full textAbstract:
碩士<br>大葉工學院<br>工業工程研究所<br>85<br>The traveling salesman problem (TSP) has been a well studied
problem for decades. TSP with more than objectives has also
attracted attention recently for its reflecting actual condition
better than single objective TSP. Due to its combinatorial
characteristic, the solution efficiency gets worse as the
problem size increases. In this research, we use Tabu Search, a
meta-heuristic, to solve both the single and multiple objective
TSP. One of the most powerful property of Tabu search is its
using flexible memory to get rid of being trapped by local
optimum when searching for the global optimum. First, some
methods suggested from literature are adopted to construct the
initial tour for TSP. Tabu search is then used to improve the
tour(solution) until optimum (or near optimum) is obtained.
For the multiple objective TSP, the augmented max-min operator
is used to generate the non-inferior solution. Additionly, an
interactive approach is used to reflect decision maker's
preference. Since the parameters setting of Tabu search would
greatly affect the solution accuracy and the solving efficiency
as well. A full factorial design is performed in this research
to find the best parameter setting to solve the TSP accurately
and efficiently.
36
林金銘. "On multi-objective single machine scheduling problem." Thesis, 1986. http://ndltd.ncl.edu.tw/handle/42009279734672073454.
Full text
37
Gunawan, Subroto. "Parameter sensitivity measures for single objective, multi-objective, and feasibility robust design optimization." 2004. http://hdl.handle.net/1903/1542.
Full textAbstract:
Thesis (Ph. D.) -- University of Maryland, College Park, 2004.<br>Thesis research directed by: Mechanical Engineering. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
38
Chen, Chun, and 陳駿. "The Multiple Trajectory Search for Single-Objective and Multi-Objective Real-Parameter Optimization." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/75696202973290252807.
Full textAbstract:
博士<br>國立中興大學<br>資訊科學與工程學系<br>102<br>Real-parameter optimization is often applied in science, electrical engineering, computer science and other fields. Real-parameter optimization can be divided into two categories: single objective real-parameter optimization and multi-objective real parameter optimization. Recently, the research on multi-objective real-parameter optimization is very active. There are many papers published on this topic. In this dissertation, a new metaheuristic method called the multiple trajectory search is proposed for real-parameter optimization. It can solve constrained single objective real-parameter optimization problems, unconstrained single objective real-parameter optimization problems, constrained multi-objective real-parameter optimization problems and unconstrained multi-objective real-parameter optimization problems. The benchmark problems proposed in the competitions held in the Congress on Evolutionary Computation 2008, 2009 and 2010 are used to test the performance of the proposed method.
Most of the metaheuristic methods do not search the solution space systematically due to their randomization characteristic. Also, most of the metaheuristic methods do not use different region search methods that are adapted to the landscape of the neighborhood of a solution. The multiple trajectory search tries to overcome these two drawbacks. Initially, it will generate solutions uniformly distributed over the solution space. When it searches the neighborhood of a solution, it will choose one of the region search methods that best fits the landscape of the neighborhood. Furthermore, at the end of each search session, solutions will be evaluated and better solutions will be put in the foreground while other solutions put in the background. And only the solutions in the foreground will be searched in the next search session, so the searching can be focused on the promising area. Revealed by the experimental results, the proposed multiple trajectory search is very competitive.
39
Huang, Ren-Jun, and 黃任駿. "Single Image Dehazing Algorithm with Two-objective Optimization." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/33776514616653182214.
Full textAbstract:
碩士<br>朝陽科技大學<br>資訊工程系<br>104<br>To record images with a camera under different climate condition, the quality of the image will be affected by the weather such as smoke, haze, rain and snow. Among them, haze is frequently an atmospheric phenomenon where dust, smoke and other dry particles obscure the clarity of the sky. In order to improve the poor quality of image due to low visibility by haze, researchers have proposed various methods to remove haze. One of them, a Proposed Dehazing Algorithm (PDA) developed by Hsieh has a good dehazing performance. However, the resulted image after dehazing changes the mood and has a poor visual sense under certain circumstance. Most dehazing performance measures are based on subjective visual to assess the pros and cons up until now. To overcome this drawback, we proposed a Proposed Optimization Dehazing Algorithm (PODA) with two-objectives evaluation, to improve the image with a good dehazing performance and maintain the mood retention. In addition, we proposed an evaluating method for dehazing image to analyze the performance of dehazing image. The developed PODA has compared with other dehazing methods using various examples. Simulation results indicate that the PODA outperforms these competing methods.
40
Taylor, James. "Objective Approaches to Single-Molecule Time Series Analysis." Thesis, 2012. http://hdl.handle.net/1911/71695.
Full textAbstract:
Single-molecule spectroscopy has provided a means to uncover pathways and heterogeneities that were previously hidden beneath the ensemble average. Such
heterogeneity, however, is often obscured by the artifacts of experimental noise and
the occurrence of undesired processes within the experimental medium. This has
subsequently caused in the need for new analytical methodologies. It is particularly
important that objectivity be maintained in the development of new analytical
methodology so that bias is not introduced and the results improperly characterized.
The research presented herein identifies two such sources of experimental uncertainty,
and constructs objective approaches to reduce their effects in the experimental results.
The first, photoblinking, arises from the occupation of dark electronic states within the
probe molecule, resulting in experimental data that is distorted by its contribution. A
method based in Bayesian inference is developed, and is found to nearly eliminate
photoblinks from the experimental data while minimally affecting the remaining data
and maintaining objectivity. The second source of uncertainty is electronic shot-noise,
which arises as a result of Poissonian photon collection. A method based in wavelet
decomposition is constructed and applied to simulated and experimental data. It is
iii
found that, while making only one assumption, that photon collection is indeed a
Poisson process, up to 75% of the shot-noise contribution may be removed from the
experimental signal by the wavelet-based procedure. Lastly, in an effort to connect
model-based approaches such as molecular dynamics simulation to model-free
approaches that rely solely on the experimental data, a coarse-grained molecular model
of a molecular ionic fluorophore diffusing within an electrostatically charged polymer
brush is constructed and characterized. It is found that, while the characteristics of the
coarse-grained simulation compare well with atomistic simulations, the model is lacking
in its representation of the electrostatically-driven behavior of the experimental system.
41
Hung, Chi-Ru, and 洪琦茹. "Ant Colony Optimization for Multi-Objective Single Machine Scheduling Problem." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/92658731992855773532.
Full textAbstract:
碩士<br>元智大學<br>工業工程與管理學系<br>93<br>Production scheduling problem is complex and difficult in real world. Delay of the orders may cause the loss of business credibility, but on the hand the too early finish-up may lead to the tremendous inventory cost. Therefore, how to plan and implement an efficient production scheduling to meet customers’ due and demands has become a very important issue to enterprises.
This research proposes several ant colony optimization algorithms with different number of colonies, pheromone updating rules, and local search mechanisms. Two objectives were considered simultaneously – minimize total weighted tardiness and minimize total weighted earliness. In order to find an efficient local heuristic for each objective, a comprehensive study of dispatching rules is employed. The COVERTAU dispatching rule is selected for the total weighted tardiness objective while the WMR rule is used to assist the optimization of total weighted earliness. Experiments were conducted to investigate the effects of the number of ants, local search, and parameter settings. Using the best parameter settings, Pareto optimal front of each algorithm is collected to compare their performance. The ant colony algorithm with five colonies, five-region local search, and a mixed pheromone updating rule outperform others. This research also hopes to provide decision-maker many practical alternatives while facing different scheduling scenarios.
42
Wang, Shih Ting, and 王詩婷. "Library of Genetic Algorithms for Single-objective Job Shop Scheduling." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/54468747062248657683.
Full text
43
Liu, Shih-Jui, and 劉師睿. "The Search Economics for Single Objective Real-Parameter Numerical Optimization." Thesis, 2019. http://ndltd.ncl.edu.tw/cgi-bin/gs32/gsweb.cgi/login?o=dnclcdr&s=id=%22107NCHU5394020%22.&searchmode=basic.
Full textAbstract:
碩士<br>國立中興大學<br>資訊科學與工程學系所<br>107<br>As a well-known continuous encoding problem, the so-called global optimization problem requires a search algorithm to contain not only the capability to do a local search but also the capability to escape from a local optimum. Several recent studies show that metaheuristic algorithms provide an effective and efficient way to solve such complex optimization problems. However, most metaheuristic algorithms may converge to particular regions after a certain number of iterations, thus falling into a local optimum. The search economics (SE) provides a possible solution to keep the search diversity during the convergence process because it will first divide the search space into a certain number of regions and then determine the search directions based on the potential (called expected value in this thesis) of each region so as to increase the search diversity. A modified SE for solving the global optimization problem, called search economics for global optimization (SEGO), is presented in this thesis. As a pioneered approach for the global optimization problem, the modified SE includes three new mechanisms---parameter adaptation, linear population size reduction, and new search strategy---and two modified mechanisms---the way the search space is divided and the way the expected value is computed. To evaluate the performance of SEGO, we compare it with four state-of-the-art search algorithms (i.e., jSO, EBOwithCMAR, ELSHADE-SPACMA, and L-SHADE-RSP) for solving 29 functions from CEC2017, based on Wilcoxon signed-ranks test and the measure of CEC2017. The experimental results show that SEGO provides a better result than all the other search algorithms compared in this thesis, especially for complex problems, e.g., high dimension functions, hybrid functions, and composition functions.
44
Croicu, Ana-Maria Hussaini M. Yousuff. "Single- and multiple-objective stochastic programming models with applications to aerodynamics." Diss., 2005. http://etd.lib.fsu.edu/theses/available/etd-11142005-102344.
Full textAbstract:
Thesis (Ph. D.)--Florida State University, 2005.<br>Advisor: M. Yousuff Hussaini, Florida State University, College of Arts and Sciences, Dept. of Mathematics. Title and description from dissertation home page (viewed Jan. 25, 2006). Document formatted into pages; contains xii, 178 pages. Includes bibliographical references.
45
Tsai, Wei-Yin, and 蔡瑋尹. "The Single Objective Optimal Tourist Traveling Planning-based on Android platform." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/6j56qp.
Full textAbstract:
碩士<br>國立臺北科技大學<br>工業工程與管理系<br>106<br>Science and technology improve every day. It brought people about the convenience of life and information exchanged immediately, and the traditional way of life will be changed in the future is inevitable. In response to the development, people’s traveling style and the operation of tourists have not been the same as in the past. Basing on network development and information circulation, the integration and analysis of tourism-related information have gradually become more popular.
This study aims to establish a set of tourist’s attractions recommendation and travel planning system, based on Android platform, to help people decide and plan their journey easily and quickly. At the beginning of the system, the user will be asked to login account or register at the first time of the system. After sign in, the user will be asked to give weight to items presented by the recommendation system. There will be a menu, the category of attractions provided by government, to be filled in. The recommendation system will do the analysis based on the weight and attraction’s rating and use the Nearest Neighbor algorithm to calculate the degree of recommendation. In view of the list of attractions, coupled with the user provide playing time and traffic method, travel planning will be the minimum traffic cost time as the target and calculate by single-objective Genetic algorithm. The result will give the user the best sequence of attractions. In the end, the sequence will be presented on the device, and compared with the sequence of random sequences to explore the benefit of the planning result.
46
Tzu-ChiehHung and 洪子頡. "Multi-objective Design and Tolerance Allocation for Single- and Multi-Level Systems." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/43455570948618164460.
Full textAbstract:
碩士<br>國立成功大學<br>機械工程學系碩博士班<br>98<br>In this work we develop a method to perform simultaneous design and tolerance allocation for engineering problems with multiple objectives. Most studies in existing literature focus on either optimal design with constant tolerances or the optimal tolerance allocation for a given design setup. Simultaneously performing both design and tolerance allocation with multiple objectives for hierarchical systems increases problem dimensions and raises additional com- putational challenges. A design framework is proposed to obtain optimal design alternatives and to rank their performances when variations are present. An optimality influence range is developed to aid design alternatives selections with an influence signal-to-noise ratio that indicates the accordance of objective variations to the Pareto set and an influence area that quantifies the variations of a design . An additional tolerance design scheme is implemented to ensure that design alternatives meet the target tolerance regions. The proposed method is also extended to decomposed multi-level systems by integrating traditional sensitivity analysis for uncertainty propagation with analytical target cascading. This work enables decision-makers to select their best design alternatives on the Pareto set using three measures with different purposes. Examples demonstrate the effectiveness of the method on both single- and multi-level systems.
47
Chao-TingTsai and 蔡昭廷. "Solving Multi-level Single-objective Decision Making Problems using Fuzzy Goal Programming." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/06920940025188920803.
Full textAbstract:
碩士<br>國立成功大學<br>工業與資訊管理學系<br>103<br>Multi-level linear programming (MLLP) is an approach that can be used to solve decision problems based on hierarchical decision structures. Satisfactions that represent the judgement of solutions obtained for a decision-maker (DM) include uncertain information. Hence, the concept of fuzzy sets is used to define the satisfaction of the corresponding value by building membership functions. This study develops a method for interpreting the relationships of satisfaction between different levels by using satisfaction intervals. To overcome the shortcomings of methods that strictly restricts the satisfaction of lower-level DMs by higher-level DMs, a more flexible decision space is proposed. The proposed model implies that satisfaction obtained of lower-level transcending the one of higher-level is allowed. An exceeding ratio (α) is proposed to provide an exceeding tolerance for lower-level DMs under some limited conditions. Moreover, linguistic variables are used to express the extra requirements of DMs that restrict the relation between adjacent levels. After integrating all constraints, fuzzy goal programming is applied. A comparison of the proposed method with other fuzzy goal programming approaches in solving multi-level programming problems shows that the proposed method achieves higher satisfaction when the middle level is difficult to satisfy. This study provides a method for interpreting the satisfaction between different levels by giving a more flexible decision space for lower-level DMs to reach higher satisfaction.
48
Chung, Chia-Lin, and 莊家林. "Develop An Intelligent Genetic Algorithm for the Multi-objective Single Machine Scheduling." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/71530412453546521148.
Full textAbstract:
碩士<br>中原大學<br>工業與系統工程研究所<br>100<br>The research focuses on multi-objects scheduling problem with one processing machine, and try to find an improved genetic algorithms. The multi-objects genetic algorithms has been studied for many years and applied to solve the schedule problem successfully, but the procrdure and the efficiency are still need to be improved. This research consider the attribute of immigrant and offered a new algorithms called intelligent genetic algorithms to solve the single machine scheduling problems. The new genetic algorithms considers the process time, lead time, delivery date and tardiness weight to find the non‐inferior solutions with best performance on total makespan and total weighted tardiness. Finally, we compare the the new genetic algorithms and the normal genetic algorithms by processing many different samples, and we find that the intelligent genetic algorithms needs more time to process, but it can find the better non‐inferior solutions with less generations.
49
Darfoun, Mohamed. "OPTIMAL DISTRIBUTED GENERATION SIZING AND PLACEMENT VIA SINGLE- AND MULTI-OBJECTIVE OPTIMIZATION APPROACHES." 2013. http://hdl.handle.net/10222/31423.
Full textAbstract:
Numerous advantages attained by integrating Distributed Generation (DG) in distribution systems. These advantages include decreasing power losses and improving voltage profiles. Such benefits can be achieved and enhanced if DGs are optimally sized and located in the systems. In this thesis, the optimal DG placement and sizing problem is investigated using two approaches. First, the optimization problem is treated as single-objective optimization problem, where the system’s active power losses are considered as the objective to be minimized. Secondly, the problem is tackled as a multi-objective one, focusing on DG installation costs. These problems are formulated as constrained nonlinear optimization problems using the Sequential Quadratic Programming method. A weighted sum method and a fuzzy decision-making method are presented to generate the Pareto optimal front and also to obtain the best compromise solution. Single and multiple DG installation cases are studied and compared to a case without DG, and a 15-bus radial distribution system and 33-bus meshed distribution system are used to demonstrate the effectiveness of the proposed methods.
50
Chen, Hsiu-Yen, and 陳修彥. "Single fluorescent molecule photobleaching detection using objective type Total Internal Reflection Fluorescence Microscopy." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/89792786749984353758.
Full textAbstract:
碩士<br>國立清華大學<br>生醫工程與環境科學系<br>94<br>In order to detect single molecule fluorescence signal, so I used total internal reflection fluorescence microscopy (TIRFM) to excite the fluorescent molecule. This setup can decrease much noise, and increase the chance of detection single fluorescent signal. Our laboratory used commercial TIRFM to combine with Dual-View and EMCCD, reached to single fluorescent molecule detection.
The sample of my experiment is single strand DNA labeled Cy3. The single strand DNA are fixed to the cover slip surface by antibody-antigen binding force. Then I used the evanescent wave by total internal reflection to excite the fluorescence, and to observe the phenomenon of single fluorescent molecule photobleaching.
In my TIRFM system, we already detected single fluorescent molecule photobleaching. In order to obtain better signal to noise ratio (SNR), I used three methods to analyze my experimental data. The method of mean value of 25 pixels in the fluorescence spot can obtain better SNR. By reducing the laser power, I detected the time of fluorescence photobleaching is increased, and the intensity of single fluorescent molecule is lowered. To enhance the time of fluorescent lifetime is important in the single molecule experiments.
I hope to observe the phenomenon of fluorescence resonance energy transfer (FRET) by using the double strands DNA labeled Cy3 and Cy5. The TIRFM system will combine with flow chamber to reach single molecule dynamical researches, and be integrated to high resolution laser tweezers system to study more biological programs in the future.