Relevant bibliographies by topics / Random search for optimum values

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers
  5. Reports

Academic literature on the topic 'Random search for optimum values'

Author: Grafiati
Published: 28 May 2022
Last updated: 31 July 2025

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Journal articles on the topic "Random search for optimum values"

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Gvasalia, Badri, and Tamar Kvachadze. "Optimum Parameters of Cylindrical Springs Calculation of Values." Works of Georgian Technical University, no. 1(535) (March 25, 2025): 199–209. https://doi.org/10.36073/1512-0996-2025-1-199-209.

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Methods of calculating the values of optimal parameters of cylindrical springs are elaborated in the paper The issues raised are presented as the tasks of non -linear mathematical programming. The stochastic method is used to show the global extremum of purpose, in particular, the random search method to find extremum. Appropriate algorithms are processed, which is realized by the algorithmic language through Visual Basic.
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Nelson, John, and J. Douglas Brodie. "Comparison of a random search algorithm and mixed integer programming for solving area-based forest plans." Canadian Journal of Forest Research 20, no. 7 (1990): 934–42. http://dx.doi.org/10.1139/x90-126.

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An area-based forest plan is formulated and solved by mixed integer programming and a random search algorithm. This is a computationally difficult problem because operational and environmental constraints require that harvest units and road projects be defined as strict binary variables. It was found that the random search algorithm could easily identify several solutions with objective function values within 10% of the true optimum. The best solution found was within 3% of the optimum. The random search algorithm is simple and can be readily implemented on the microcomputer. It is concluded t
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Valsta, Lauri T. "A comparison of numerical methods for optimizing even aged stand management." Canadian Journal of Forest Research 20, no. 7 (1990): 961–69. http://dx.doi.org/10.1139/x90-129.

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A two-species, whole-stand, deterministic growth model was combined with three optimization methods to derive management regimes for species composition, thinnings, and rotation age, with the objective of maximizing soil expectation value. The methods compared were discrete time – discrete state dynamic programming, direct search using the Hooke and Jeeves algorithm, and random search. Optimum solutions for each of the methods varied considerably, required unequal amounts of computational time, and were not equally stable. Dynamic programming located global optimal solutions but did not determ
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Lee, Kang Seok, and Jin Kyu Song. "Configuration Optimization of Truss Structures Using Harmony Search Heuristic Algorithm." Advanced Materials Research 26-28 (October 2007): 793–96. http://dx.doi.org/10.4028/www.scientific.net/amr.26-28.793.

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Most structural optimization methods are based on mathematical algorithms that require substantial gradient information. The selection of the starting values is also important to ensure that the algorithm converges to the global optimum. This paper describes a new structural configuration optimization method based on the harmony search (HS) meta-heuristic algorithm. The HS algorithm does not require initial values and uses a random search instead of a gradient search, so derivative information is unnecessary. A benchmark truss example is presented to demonstrate the effectiveness and robustnes
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Zhao, Ji, Yi Fu, and Juan Mei. "An improved dynamic cooperative random drift particle swarm optimization algorithm based on search history decision." Journal of Algorithms & Computational Technology 14 (January 2020): 174830262097353. http://dx.doi.org/10.1177/1748302620973537.

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A novel dynamic cooperative random drift particle swarm optimization algorithm based on entire search history decision (CRDPSO) is reported. At each iteration, the positions and the fitness values of the evaluated solutions in the algorithm are stored by a binary space partitioning tree structure archive, which leads to a fast fitness function approximation. The mutation is adaptive and parameter-less because of the fitness function approximation enhancing the mutation strategy. The dynamic cooperation between the particles by using the context vector increases the population diversity helps t
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Pan, Ying, Dong Juan Xue, Tian Yi Gao, Li Bin Zhou, and Xiao Yu Xie. "A Modified Adaptive Genetic Algorithm for the Flexible Job-Shop Scheduling Problem." Applied Mechanics and Materials 401-403 (September 2013): 2037–43. http://dx.doi.org/10.4028/www.scientific.net/amm.401-403.2037.

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Combined with the stage-related characteristics in solving process of the Flexible Job-shop Scheduling Problem (FJSP) and the evolution characteristics of Genetic Algorithm (GA), a modified Adaptive Genetic Algorithm based on iterative generation and analysis of fitness values distribution is presented in this paper, which has both methods advantages. Instance simulation verifies that the FJSPs own characteristics are utilized in its solution by using the modified AGA, which overcomes traditional GAs limitation that initial stage of evolution is early and random search of medium-late stage is
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Savran, Melih, Mücahit Osman Türkan, Mustafa Öncül, and Levent Aydın. "Optimization of drilling parameters for minimizing delamination factor in biocomposites using multiple nonlinear neuro-regression and stochastic methods." Journal of Innovative Engineering and Natural Science 5, no. 1 (2024): 225–42. https://doi.org/10.61112/jiens.1564284.

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In this study, a novel design optimization strategy is proposed to enhance the drilling performance of HDPE/Washingtonia fiber biocomposites, considering operational parameters such as drill diameter (d), feed rate (f), and spindle speed (N). A detailed investigation utilizing multiple nonlinear neuro-regression analyses is conducted to predict the delamination factor (Fd), based on a dataset obtained from a literature study. 14 candidate mathematical functions are suggested for modelling, and their accuracy is assessed through R2training, R2testing, and R2validation metrics, and boundedness c
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ÖZDAMAR, LINET, and CHANDRA SEKHAR PEDAMALLU. "NEW SIMULATED ANNEALING ALGORITHMS FOR CONSTRAINED OPTIMIZATION." Asia-Pacific Journal of Operational Research 27, no. 03 (2010): 347–67. http://dx.doi.org/10.1142/s0217595910002740.

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We propose a Population based dual-sequence Non-Penalty Annealing algorithm (PNPA) for solving the general nonlinear constrained optimization problem. The PNPA maintains a population of solutions that are intermixed by crossover to supply a new starting solution for simulated annealing throughout the search. Every time the search gets stuck at a local optimum, this crossover procedure is triggered and simulated annealing search re-starts from a new subspace. In both the crossover and simulated annealing procedures, the objective function value and the total solution infeasibility degrees are t
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Sharma, Rakesh Chandmal, Sakshi Sharma, Sunil Kumar Sharma, Neeraj Sharma, and Gurpreet Singh. "Analysis of bio-dynamic model of seated human subject and optimization of the passenger ride comfort for three-wheel vehicle using random search technique." Proceedings of the Institution of Mechanical Engineers, Part K: Journal of Multi-body Dynamics 235, no. 1 (2021): 106–21. http://dx.doi.org/10.1177/1464419320983711.

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Ride comfort is the major concern to the roadway vehicle passengers, travelling in as it affects their health and efficiency to work. In the present study, a 9 DoF model of a three-wheel vehicle is developed with Lagrangian approach to investigate its ride behavior when subjected to random surface irregularities. The irregularities of the track are measured with a three-wheeled setup equipped with profilometer known as opto-coupler. The present model is validated in two ways, first by comparing the vertical-lateral PSD acceleration received from simulation and actual testing and second by comp
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Abramzon, Boris. "Numerical Optimization of the Thermoelectric Cooling Devices." Journal of Electronic Packaging 129, no. 3 (2006): 339–47. http://dx.doi.org/10.1115/1.2753959.

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The present study proposes a unified numerical approach to the problem of optimum design of the thermoelectric devices for cooling electronic components. The standard mathematical model of a single-stage thermoelectric cooler (TEC) with constant material properties is employed. The model takes into account the thermal resistances from the hot and cold sides of the TEC. Values of the main physical parameters governing the TEC performance (Seebeck coefficient, electrical resistance, and thermal conductance) are derived from the manufacturer catalog data on the maximum achievable temperature diff
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Dissertations / Theses on the topic "Random search for optimum values"

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Бебех, Я. С. "Комп’ютерна система пошуку оптимальних параметрів магнітного тахометричного підсилювача". Master's thesis, Сумський державний університет, 2018. http://essuir.sumdu.edu.ua/handle/123456789/72166.

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Розроблено алгоритм і комп’ютерну програму для пошуку оптимальних параметрів магнітного тахометричного підсилювача. Їхня робота перевірена на контрольному прикладі. Програма може бути застосована при проектуванні цих підсилювачів.
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Горобей, О. О. "Інформаційна технологія комп'ютерного моделювання мікроклімату у теплицях". Master's thesis, Сумський державний університет, 2018. http://essuir.sumdu.edu.ua/handle/123456789/72186.

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Book chapters on the topic "Random search for optimum values"

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Uher Vojtěch, Gajdoš Petr, Radecký Michal, and Snášel Václav. "A Novel Approach of Applying the Differential Evolution to Spatial Discrete Data." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2016. https://doi.org/10.3233/978-1-61499-672-9-1555.

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The Differential Evolution (DE) is a powerful bio-inspired algorithm searching optimal solutions. The actual DE modifications can handle the real, integer and discrete valued problems. The values of the discrete-valued variables represent the integer indices addressing the discrete samples in the ordered array. The optimization in unordered samples leads to a random search. This paper proposes a novel modification dealing with d-dimensional discrete vertices. A vertex hashing is used to strengthen the local properties of a dataset and to improve the spatial convergence of the evolution.
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S., Parvathavarthini, Karthikeyani Visalakshi N., Shanthi S., and Lakshmi K. "Crow-Search-Based Intuitionistic Fuzzy C-Means Clustering Algorithm." In Developments and Trends in Intelligent Technologies and Smart Systems. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3686-4.ch007.

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Data clustering is an unsupervised technique that segregates data into multiple groups based on the features of the dataset. Soft clustering techniques allow an object to belong to various clusters with different membership values. However, there are some impediments in deciding whether or not an object belongs to a cluster. To solve these issues, an intuitionistic fuzzy set introduces a new parameter called hesitancy factor that contributes to the lack of domain knowledge. Unfortunately, selecting the initial centroids in a random manner by any clustering algorithm delays the convergence and
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Shadab, Mohd, MD Saqib Javed, Mohammad Sajid, Mukesh Prasad, Maria A. Lapina, and Mikhail Babenko. "Generating Highly Nonlinear S-Boxes Using a Hybrid Approach With Particle Swarm Optimization." In Advances in Computer and Electrical Engineering. IGI Global, 2024. https://doi.org/10.4018/979-8-3693-6834-3.ch001.

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A substitution box (S-box) is a fundamental component in cryptographic algorithms that enhance data security by providing a complex mapping between input and output values. S-box strengthens the encryption and decryption process by introducing nonlinearity and protecting the encrypted data against various differential and linear cryptanalytic attacks. The problem of generating an S-box with optimal properties is challenging and falls under the category of NP-Hard problems. This study proposes a hybrid approach combining the Particle Swarm optimization algorithm (PSO) and the Booster algorithm
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Dave, Tirth Vishalbhai, Sajidha S. A., M. Nivedita, and Aakif Mairaj. "Seasonal Prediction of Hybrid Renewable Energy Using Weighted Ensemble Algorithm With Optimal Allocation on Demand." In Leveraging IoT and Machine Learning for Smart Urban Planning. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-9030-6.ch004.

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Numerous amounts of work towards optimal hybrid energy allocation using PSO, HG-PSO, GA, HOMER-Pro-Software, multi-objective PSO, and many algorithms have been effectively applied. Challenges posed by seasonal variations in solar and wind power generation have not been addressed so far. A novel method of seasonal prediction of hybrid energy and optimal allocation using weighted ensembled ML models and optimization algorithms is proposed. Algorithms such as Decision Trees, Random Forest, K-Nearest Neighbors, XG Boost, Lasso Regression, and Ridge Regression are evaluated for accuracy based on wh
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Atkinson, A. C., and A. N. Doney. "Some key ideas." In Optimum Experimental Designs. Oxford University PressOxford, 1992. http://dx.doi.org/10.1093/oso/9780198522546.003.0002.

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Abstract Figure 2.1 is one schematic representation of an experiment. A single trial consists of measuring the values of the t response, or output, variables y 1, …, Y t. These values are believed to depend upon the value of the m factors or explanatory variables u1 … um. However, the relationship is obscured by the presence of unobservable random errors ε 1, ... , ε 1,.
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Aydın, Yaren, Sinan Melih Nigdeli, Gebrail Bekdaş, Sanghun Kim, and Zong Woo Geem. "A Review of Metaheuristic-Based Optimum Design of Reinforced Concrete Structures." In Advanced Optimization Applications in Engineering. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-2161-4.ch006.

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With the increase in environmentally friendly approaches, it has been studied for the optimum design of reinforced concrete components that contain cement and steel with high CO2 emissions and high cost. In this study, the minimum cost and CO2 emission of rectangular reinforced concrete columns under uniaxial bending are aimed. Since it has two different objectives, harmony search (HS) was used for multi-objective optimization. The rules used in rectangular reinforced concrete columns under uniaxial bending were followed by ACI 318: Building code requirements for structural concrete. In this c
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Banu, P. K. Nizar, and S. Andrews Samraj. "Swarm-Based Clustering for Gene Expression Data." In Bio-Inspired Computing for Information Retrieval Applications. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-2375-8.ch005.

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Clustering is one of the most important techniques, which group genes of similar expression pattern into a small number of meaningful homogeneous groups or clusters. Gene expression data has certain special characteristics and is a challenging research problem. There are many applications for clustering gene expression data. Clustering can be applied for genes called gene clustering. Hard clustering allows a gene to get placed in exactly one cluster and converges in local optima. Soft clustering approach allows gene to get placed in all the clusters with some membership values. As the hard clu
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"Metaheuristic Optimization of Reinforced Concrete Footings." In Metaheuristic Approaches for Optimum Design of Reinforced Concrete Structures. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-2664-4.ch005.

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Footings are one of the structural members, which is one of the complex engineering problems to optimize. Differently from the other reinforced concrete member designs such as beams and columns, geotechnical limit states are also needed to consider in addition to structural state limits. In this chapter, the optimum design of RC footing is presented according to ACI 318: Building code requirements for structural concrete. The optimum results of methodologies employing different algorithms including Harmony Search (HS), Teaching-Learning-Based Optimization algorithm (TLBO), and Flower Pollinati
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Rahmani, Shima, Elyas Fadakar, and Masoud Ebrahimi. "An Efficient Quantile-Based Adaptive Sampling RBDO with Shifting Constraint Strategy." In Avantgarde Reliability Implications in Civil Engineering [Working Title]. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.110442.

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There is an increasing demand for the performance optimization under the reliability constraints in various engineering problems. These problems are commonly known as reliability-based design optimization (RBDO) problems. Among different RBDO frameworks, the decoupled methods are widely accepted for their high efficiency and stability. However, when facing problems with high nonlinearity and nonnormally distributed random variables, they lose their computational performance. In this study, a new efficient decoupled method with two level quantile-based sampling strategy is presented. The strate
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Mendes, Rui P. G., Maria do Rosário Alves Calado, and Sílvio José Mariano. "Particle Swarm Optimization Method to Design a Linear Tubular Switched Reluctance Generator." In Advances in Computational Intelligence and Robotics. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-8291-7.ch015.

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In this chapter, the Particle Swarm Optimization method is applied to four different structural configurations of a linear switched reluctance generator with tubular topology. The optimization process involves the search of the values for a defined set of geometric parameters that maximize the rate of change of the generator's inductance with the relative displacement of its mover part. The optimization algorithm is applied to each structural configuration in order to find the optimum geometry as well to identify the most suitable configuration for electric generation.
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Conference papers on the topic "Random search for optimum values"

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Abramzon, B. "Numerical Optimization of the Thermoelectric Cooling Devices." In ASME 2005 Summer Heat Transfer Conference collocated with the ASME 2005 Pacific Rim Technical Conference and Exhibition on Integration and Packaging of MEMS, NEMS, and Electronic Systems. ASMEDC, 2005. http://dx.doi.org/10.1115/ht2005-72686.

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The present study proposes the unified numerical approach to the problem of optimum design of the thermoelectric devices for cooling electronic components. The method is illustrated with several examples which are based on the standard mathematical model of a single-stage thermoelectric cooler with constant material properties. The model takes into account the thermal resistances from the hot and cold sides of the TEC. Values of the main physical parameters governing the TEC performance (Zeebeck coefficient, electrical resistance and thermal conductance) are derived from the manufacturer catal
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Du, Liu, and Kyung K. Choi. "An Inverse Analysis Method for Design Optimization With Both Statistical and Fuzzy Uncertainties." In ASME 2006 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/detc2006-99731.

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Structural analysis and design optimization have recently been extended to consider various uncertainties. If the statistical data for the uncertainties are sufficient to construct the input distribution function, the uncertainties can be treated as random variables and RBDO is used; otherwise, the uncertainties can be treated as fuzzy variables and PBDO is used. However, many structural design problems include both uncertainties with sufficient data and uncertainties with insufficient data. For these problems, RBDO will yield an unreliable design since the distribution functions of uncertaint
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Tsugawa, Takuji. "Search of High Efficiency Design by Another Specific Speed Design." In ASME-JSME-KSME 2019 8th Joint Fluids Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/ajkfluids2019-4645.

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Abstract Quite a lot of design parameters exist when the designer designs the best performance impeller and guidevane. Finally, it is necessary to decide the detail 3D shape of impeller and guidevane. The best flow conditions of the flow velocity and the flow angle at the impeller inlet and outlet are designed as first step before impeller detailed 3D shape is designed. The detailed 3D shape is not necessary in this study. The optimum meridian shape has been found, assuming that the total loss head is addition of the blade-to-blade diffusion loss head and the hub-tip axial-symmetrical annular
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Gao, Yansong, and Jie Zhang. "Average-case Analysis of the Assignment Problem with Independent Preferences." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/41.

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The fundamental assignment problem is in search of welfare maximization mechanisms to allocate items to agents when the private preferences over indivisible items are provided by self-interested agents. The mainstream mechanism \textit{Random Priority} is asymptotically the best mechanism for this purpose, when comparing its welfare to the optimal social welfare using the canonical \textit{worst-case approximation ratio}. Surprisingly, the efficiency loss indicated by the worst-case ratio does not have a constant bound \cite{FFZ:14}.Recently, \cite{DBLP:conf/mfcs/DengG017} shows that when the
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Shin, Jaekwan, and Scott Ferguson. "Product Line Design Search Considering Reliability and Robustness Under Uncertainty in Discrete Choice Methods." In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-59535.

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Point-estimates of part-worth values in customer preference models have been used in market-based product design under the simplying assumption that customer preferences can be treated as deterministic. However, customer preferences are not only inherently stochastic, but are also statistical estimates that exhibit random errors in model formulation and estimation. Ignoring uncertainty in customer preferences and variability in estimates has caused concern about the reliability and robustness of an optimal product design solution. This study quantitatively defines reliability and robustness of
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Han, Yun, and Marc P. Mignolet. "Optimization of Intentional Mistuning Patterns for the Mitigation of the Effects of Random Mistuning." In ASME Turbo Expo 2008: Power for Land, Sea, and Air. ASMEDC, 2008. http://dx.doi.org/10.1115/gt2008-51439.

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This paper focuses on the optimization of intentional mistuning patterns for the reduction of the sensitivity of the forced response of bladed disks to random mistuning. Intentional mistuning is achieved here by using two different blade types (denoted as A and B) around the disk. It is thus desired to find the arrangement of these A and B blades (A/B pattern) that leads to the smallest 99th percentile of the amplitude of blade response in the presence of random mistuning. It is first demonstrated that there usually is a large number of local minima and further that the cost of a function eval
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Aydın, Kemal Bartu, Levent Aydin, and Fethullah Güneş. "Stochastic Optimization of TiO2-Graphene Nanocomposite by Using Neuro-Regression Approach for Maximum Photocatalytic Degradation Rate." In International Students Science Congress. Izmir International Guest Student Association, 2021. http://dx.doi.org/10.52460/issc.2021.044.

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TiO2 is one of the most common materials for photocatalytic applications due to its stability, affordability, and photoactive efficiency. However, it has some drawbacks, such as limited solar radiation response and quick recombination of excitons. Using graphene could be one of the methods to enhance the photocatalytic properties of TiO2. This study intends to optimize the photocatalytic performance of TiO2/Graphene (TiO2/G) nanocomposite by using neuro-regression analysis. In the analysis, the effect of some hydrothermal synthesis parameters, namely, amount of graphene oxide, ethanol/water ra
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Khan, Mohammad Rasheed, Shams Kalam, Abdul Asad, and Sidqi A. Abu-khamsin. "Development of a Deterministic Total Organic Carbon (TOC) Predictor for Shale Reservoirs." In SPE EuropEC - Europe Energy Conference featured at the 84th EAGE Annual Conference & Exhibition. SPE, 2023. http://dx.doi.org/10.2118/214383-ms.

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Abstract Unconventional reservoirs like shale oil/gas are expected to play a major role in many unexplored regions, globally. Shale resource evaluation involves the estimation of Total Organic Carbon (TOC) which correlates to the prospective capability of generating and containing hydrocarbons. Direct measurement of TOC through geochemical analysis is often not feasible, and hence researchers have focused on indirect methods to estimate TOC using analytical and statistical techniques. Accordingly, this work proposes the application of artificial intelligence (AI) techniques to leverage routine
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Khan, Mohammad Rasheed, Shams Kalam, Abdul Asad, and Sidqi A. Abu-khamsin. "Development of a Deterministic Total Organic Carbon (TOC) Predictor For Shale Reservoirs." In Middle East Oil, Gas and Geosciences Show. SPE, 2023. http://dx.doi.org/10.2118/213350-ms.

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Abstract Unconventional reservoirs like shale oil/gas are expected to play a major role in many unexplored regions, globally. Shale resource evaluation involves the estimation of Total Organic Carbon (TOC) which correlates to the prospective capability of generating and containing hydrocarbons. Direct measurement of TOC through geochemical analysis is often not feasible, and hence researchers have focused on indirect methods to estimate TOC using analytical and statistical techniques. Accordingly, this work proposes the application of artificial intelligence (AI) techniques to leverage routine
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Aberšek, Boris, and Metka Kordigel Aberšek. "EDUCATION TRANSFORMATION FOR NET GENERATION." In Proceedings of the 6th International Baltic Symposium on Science and Technology Education (BalticSTE2025). Scientia Socialis Press, 2025. https://doi.org/10.33225/balticste/2025.11.

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When life (society) changes rapidly and drastically, school (education) must change accordingly. However, not all changes are good and beneficial for society, so schools must also think critically and work with a time lag that allows for critical reflection and the search for more rational and optimal solutions. Teachers remain essential in the educational process, but their role changes drastically. This shift should not stem from random decisions by inventive individuals but rather from carefully considered reflections on new pedagogical paradigms. Today, this is called digital pedagogy, whi
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Reports on the topic "Random search for optimum values"

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Ungar, Eugene D., Montague W. Demment, Uri M. Peiper, Emilio A. Laca, and Mario Gutman. The Prediction of Daily Intake in Grazing Cattle Using Methodologies, Models and Experiments that Integrate Pasture Structure and Ingestive Behavior. United States Department of Agriculture, 1994. http://dx.doi.org/10.32747/1994.7568789.bard.

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This project addressed the prediction of daily intake in grazing cattle using methodologies, models and experiments that integrate pasture structure and ingestive behavior. The broad objective was to develop concepts of optimal foraging that predicted ingestive behavior and instantaneous intake rate in single and multi-patch environments and extend them to the greater scales of time and space required to predict daily intake. Specific objectives included: to determine how sward structure affects the shape of patch depletion curves, to determine if the basic components of ingestive behavior of
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