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Journal articles on the topic 'Multi-Methods strategy'

Author: Grafiati

Published: 4 June 2021

Last updated: 6 February 2022

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1

Čabala, Ján, and Ján Jadlovský. "Choosing the Optimal Production Strategy by Multi-Objective Optimization Methods." Acta Polytechnica Hungarica 17, no. 5 (2020): 7–26. http://dx.doi.org/10.12700/aph.17.5.2020.5.1.

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Li, Luoqing, Chuanwu Yang, and Qiwei Xie. "1D embedding multi-category classification methods." International Journal of Wavelets, Multiresolution and Information Processing 14, no. 02 (March 2016): 1640006. http://dx.doi.org/10.1142/s0219691316400063.

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In this paper, we propose a novel semi-supervised multi-category classification method based on one-dimensional (1D) multi-embedding. Based on the multiple 1D embedding based interpolation technique, we embed the high-dimensional data into several different 1D manifolds and perform binary classification firstly. Then we construct the multi-category classifiers by means of one-versus-rest and one-versus-one strategies separately. A weight strategy is employed in our algorithm for improving the classification performance. The proposed method shows promising results in the classification of handwritten digits and facial images.

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Wang, Mingshen, and Jenshou Yang. "A multi‐criterion experimental comparison of three multi‐attribute weight measurement methods." Journal of Multi‐Criteria Decision Analysis 7, no. 6 (November 1998): 340–50. http://dx.doi.org/10.1002/(sici)1099-1360(199811)7:6<340::aid-mcda206>3.0.co;2-s.

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Mozaffari, Ahmad. "Synchronous self-learning Pareto strategy." International Journal of Intelligent Computing and Cybernetics 11, no. 2 (June 11, 2018): 197–233. http://dx.doi.org/10.1108/ijicc-05-2017-0050.

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Purpose In recent decades, development of effective methods for optimizing a set of conflicted objective functions has been absorbing an increasing interest from researchers. This refers to the essence of real-life engineering systems and complex natural mechanisms which are generally multi-modal, non-convex and multi-criterion. Until now, several deterministic and stochastic methods have been proposed to cope with such complex systems. Advanced soft computational methods such as evolutionary games (cooperative and non-cooperative), Pareto-based techniques, fuzzy evolutionary methods, cooperative bio-inspired algorithms and neuro-evolutionary systems have effectively come to the aid of researchers to build up efficient paradigms with application to vector optimization. The paper aims to discuss this issue. Design/methodology/approach A novel hybrid algorithm called synchronous self-learning Pareto strategy (SSLPS) is presented for the sake of vector optimization. The method is the ensemble of evolutionary algorithms (EA), swarm intelligence (SI), adaptive version of self-organizing map (CSOM) and a data shuffling mechanism. EA are powerful numerical optimization algorithms capable of finding a global extreme point over a wide exploration domain. SI techniques (the swarm of bees in our case) can improve both intensification and robustness of exploration. CSOM network is an unsupervised learning methodology which learns the characteristics of non-dominated solutions and, thus, enhances the quality of the Pareto front. Findings To prove the effectiveness of the proposed method, the authors engage a set of well-known benchmark functions and some well-known rival optimization methods. Additionally, SSLPS is employed for optimal design of shape memory alloy actuator as a nonlinear multi-modal real-world engineering problem. The experiments show the acceptable potential of SSLPS for handling both numerical and engineering multi-objective problems. Originality/value To the author’s best knowledge, the proposed algorithm is among the rare multi-objective methods which fosters the use of automated unsupervised learning for increasing the intensity of Pareto front (while preserving the diversity). Also, the research evaluates the power of hybridization of SI and EA for efficient search.

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Cahyaningsih, Elin, Dana Indra Sensuse, and Handrie Noprisson. "Multi Methods for Knowledge Management Strategy Roadmap of Government Human Capital Management." Procedia Computer Science 124 (2017): 496–503. http://dx.doi.org/10.1016/j.procs.2017.12.182.

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Lee, Sang-Hun, Sung-Geon Song, and Sung-Jun Park. "Low Frequency Multi-Level Switching Strategy Based on Phase-Shift Control Methods." Journal of international Conference on Electrical Machines and Systems 1, no. 3 (September 1, 2012): 366–71. http://dx.doi.org/10.11142/jicems.2012.1.3.366.

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Shu-sheng, Chen, Hua Yang, Cai Fang-jie, and Gao Zheng-hong. "Multi-dimensional dissipation strategy within advection upstream splitting methods in hypersonic flows." Journal of Physics: Conference Series 1786, no. 1 (February 1, 2021): 012050. http://dx.doi.org/10.1088/1742-6596/1786/1/012050.

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CHOUDHURY, B. B., and B. B. BISWAL. "ALTERNATIVE METHODS FOR MULTI-ROBOT TASK ALLOCATION." Journal of Advanced Manufacturing Systems 08, no. 02 (December 2009): 163–76. http://dx.doi.org/10.1142/s0219686709001717.

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One of the most important aspects in the design of multi-robot systems (MRS) is the allocation of tasks among the robots in a productive and efficient manner. This paper presents an empirical study on task allocation strategies in multirobot environment. In general, optimal solutions are found through an exhaustive search, but because there are n × m ways in which m tasks can be assigned to n robots, an exhaustive search is often not possible with increased number of tasks. Task allocation methodologies for multirobot systems are developed by considering their capability in terms of time and space. The present work adopts a two-phase methodology to allocate tasks optimally amongst the candidate robots. The allocation cost of the robots is determined during the first phase and alternate algorithms are used in the second phase for optimizing the allocation. The work considers systems of practical sizes and the results obtained through this are helpful in recommending appropriate techniques to the users of MRS for increasing producibility and robot utilization. Three different approaches using Linear programming, Hungarian Algorithm and Knapsack Algorithm are presented and their results are analyzed for the suitability of the methods for an allocation problem. Simulation results are presented and compared for the benefit of the users.

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Ture, Hasan, Seyyide Dogan, and Deniz Kocak. "Assessing Euro 2020 Strategy Using Multi-criteria Decision Making Methods: VIKOR and TOPSIS." Social Indicators Research 142, no. 2 (June 4, 2018): 645–65. http://dx.doi.org/10.1007/s11205-018-1938-8.

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Lieberman, Elliot R. "Soviet Multi-Objective Mathematical Programming Methods: An Overview." Management Science 37, no. 9 (September 1991): 1147–65. http://dx.doi.org/10.1287/mnsc.37.9.1147.

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Chen, Dong Jiao, Jia Yan Chen, Xiao Qing Shen, and Zhang Wei Chen. "Control Strategy for Multi-Exciter Random Vibration Test." Applied Mechanics and Materials 141 (November 2011): 33–38. http://dx.doi.org/10.4028/www.scientific.net/amm.141.33.

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Multi-exciter vibration can provide greater thrust for overweight test specimen, achieve the uniformity of vibration for the special structure of the thin specimen, and overcome the shortcomings in single-exciter test, it becomes the trend of vibration test. Based on the control theory of multi-exciter vibration test, a system equilibrium synthesis is presented to make up for deficiencies of different methods for random vibration test control algorithm. the relevant experimental study is carried out on the experimental platform, experimental results show that dynamic control range of multi-exciter random vibration control system achieves 90dB in the self closed-loop control test. high precision is reached for self-spectrum control of actual test system after establishing multiple shaker, self-spectrum of control response is controlled in the range of ± 1.5dB, which satisfies requirements in engineering test.

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Sho, Hiroshi. "Expansion of Particle Multi-Swarm Optimization." Artificial Intelligence Research 7, no. 2 (December 27, 2018): 74. http://dx.doi.org/10.5430/air.v7n2p74.

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For improving the search ability and performance of elementary multiple particle swarm optimizers, we, in this paper, propose a series of multiple particle swarm optimizers with information sharing by introducing a special strategy,called multi-swarm information sharing. The key idea, here, is to add a special confidence term into the updating rule of the particle's velocity by the best solution found out by the particle multi-swarm search. This is a new type approach for the technical development and evolution of particle multi-swarm optimization itself. In order to confirm the effectiveness of the information sharing strategy in the proposed particle multi-swarm search, several computer experiments of dealing with a suite of benchmark problems are carried out. For investigating the performance and efficiency of these proposed methods, we compare their search ability and performance, respectively. The obtained experimental results show that the proposed methods have better search ability and performance than those methods without the strategy. And we still decide the best value of adding the new confidence coefficient to the multi-swarm for dealing with the given optimization problems.

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Berezhna, Lesya, and Oksana Snytuk. "RATING ASSESSMENT IN MAKING FINANCIAL DECISIONS BY METHODS OF MULTI-CRITERIA ANALYSIS." Proceedings of Scientific Works of Cherkasy State Technological University Series Economic Sciences, no. 60 (April 19, 2021): 60–71. http://dx.doi.org/10.24025/2306-4420.1.60.2021.227591.

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The article attempts to reveal the problems of decision support processes by consumers of banking services. Choosing the best financial strategy always requires significant mathematical tools. The comparison of methodological tools for making management decisions has allowed us to identify groups of methods. The most common among them are game theory, multidimensional ranking and multi-criteria analysis, a fairly modern method exploring alternative options using multi-objective optimization without certain shortcomings of the first two methods. The main purpose of the study is to adapt the methods of multi-criteria analysis and to form universal tools to substantiate management decisions on the optimal financial strategy. We suggest a methodological approach based on the use of multi-criteria assessment tools, for the rating assessment of possible alternatives in making financial decisions, namely Smart method to determine the weighting factors of the evaluation criteria and TOPSIS method to assess the optimum banking institution from the perspective of bank depositors. The article pays special attention to highlighting and describing the hierarchy of the task of choosing a depository financial institution and the main features of strategic alternatives. To assess the banks’ ratings we set up the system of generalized criteria including three groups, each of which by means of decomposition is divided into 11 partial criteria, which have monotonically increasing target functions (except for "additional associated costs"). Initial data in the form of a constructed "decision matrix" according to certain particular criteria are formed on the basis of statistical and expert information. We have chosen the end of 2020 ‒ beginning of 2021 as the research period for utilizing up-to-date information. The research of rating assessment in the article is carried out in the following logical sequence: analysis of existing methods of financial decision-making support and the significance of modern methods of multi-criteria analysis among them, a thorough problem statement from the perspective of the banks’ services consumers, singling out the list of alternatives and their estimation criteria, substantiating the values of the weighting coefficients of generalized and particular criteria by the SMART method, practical application of the TOPSIS method algorithm to select the best alternative and recommendations for making a financial decision. Therefore by means of mathematical calculations the article justifies the choice of the optimum strategy by a consumer of financial services of the banking institution offering the most attractive conditions for opening an account. Thus, the study empirically confirms and theoretically proves that the use of modern economic and mathematical methods, in particular the TOPSIS method, helps the consumer of banking services in supporting of making well-considered and optimum management decisions, taking into account the previously set evaluation criteria.

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Geldermann, Jutta, and Anita Schöbel. "On the Similarities of Some Multi-Criteria Decision Analysis Methods." Journal of Multi-Criteria Decision Analysis 18, no. 3-4 (May 2011): 219–30. http://dx.doi.org/10.1002/mcda.468.

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Blasco-Blasco, Olga, Marina Liern-García, Aarón López-García, and Sandra E. Parada-Rico. "An Academic Performance Indicator Using Flexible Multi-Criteria Methods." Mathematics 9, no. 19 (September 26, 2021): 2396. http://dx.doi.org/10.3390/math9192396.

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Composite indicators are a very useful tool for conveying summary information on the overall performance of institutions and facilitating decision-making. Increasingly, there is a demand for indicators that allow performance to be assessed after the implementation of a strategy. This has several difficulties, and in this paper, we address three of them: how to evaluate at different points in time, how to estimate the weighting of the criteria and how to normalize the data. Our proposal is based on multicriteria techniques, using a recent method, uwTOPSIS, and is applied to data collected from 2975 students enrolled in the first year of science and engineering at the Industrial University of Santander (Colombia) from the first semester of 2016 to the first semester of 2019. In the paper, we show that our proposal makes it possible to measure and evaluate the academic performance of students at two points in time, and this allows the University to know whether its student support policy has been successful and to what degree it has been effective. Due to the large amount of data handled, data management has been done using R programming language, and model implementation has been done with Python.

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Han, Ding, and Jian Rong Zheng. "Solving Expensive Multi-Objective Optimization Problems by Kriging Model with Multi-Point Updating Strategy." Applied Mechanics and Materials 685 (October 2014): 667–70. http://dx.doi.org/10.4028/www.scientific.net/amm.685.667.

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A method which utilizes Kriging model and a multi-point updating strategy is put forward for solving expensive multi-objective optimization problems. Assisted by a defined cheaper multi-objective optimization problem and a maximum average distance criterion, multiple updating points can be found. The proposed method is tested on two numerical functions and a ten-bar truss problem, the results show that the proposed method is efficient in obtaining Pareto optimal solutions with good convergence and diversity when the same computation resource is used comparing with two other methods.

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Ding, Siew-Hong, and Shahrul Kamaruddin. "Assessment of distance-based multi-attribute group decision-making methods from a maintenance strategy perspective." Journal of Industrial Engineering International 11, no. 1 (July 30, 2014): 73–85. http://dx.doi.org/10.1007/s40092-014-0078-2.

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Piórkowska, Katarzyna. "Behavioural strategy: Adaptability context." Management 20, no. 1 (May 1, 2016): 256–76. http://dx.doi.org/10.1515/manment-2015-0038.

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SummaryThe paper is embedded in the following fields: strategic management in terms of behavioural strategy concept, adaptability construct, and micro-foundations realm as well as organizational theory and psychology. Moreover, the paper concerns to some extent a multi-level approach in strategic management involving individual, team, and organizational level. The aim of the paper is to contribute to extend, on one hand, the ascertainment set in the field of behavioural strategy as behavioural strategy encompasses a mindboggling diversity of topics and methods and its conceptual unity has been hard to achieve (Powell, Lovallo, Fox 2011, p. 1371), and on the other hand, to order mixed approaches to adaptability especially to gain insights on micro-level adapting processes (individual adaptability and adaptive performance) in terms of the multi-level approach. The method that has been used is literature studies and the interference is mostly deductive. The structure of the manuscript is four-fold. The first part involves the considerations in the field of adaptability and adaptive performance at the individual level. The issues of adaptability and adaptive performance at the team level have been presented in the second part. The third part encompasses the organizational adaptability assertions. Finally, the conclusion, limitations of the considerations highlighted as well as the future research directions have been emphasized. The overarching key finding is that the behavioural strategy concept may constitute the boundary spanner in exploring and explaining adaptability phenomenon at different levels of analysis.

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Liu, Xuan, Hua Bian, Hong Wu Chen, and Li Jie Zhao. "The Comprehensive, Effective Purification Strategy of Carbon Nanotubes." Key Engineering Materials 531-532 (December 2012): 450–53. http://dx.doi.org/10.4028/www.scientific.net/kem.531-532.450.

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It is known that the high purity of carbon nanotubes (CNTs) are hard to obtain because of the impurities, which directly affect their unique properties and potential applications. Some modern purification methods including physical separation methods and chemical oxidation methods have been developed for getting the CNTs. But either way, each method still has some deficiencies, such as structure damaged, complex steps and low yield. Now there is a comprehensive multi-step method to overcome this predicament, it combines the air oxidation, hydrochloric acid treatment, SDS dispersion, centrifugation process, mixed acid oxidation and H2O2 oxidation. In this paper, the whole procedures of comprehensive methods are discussed in detail.

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Zhang, Shun, Jianlin Jiang, Su Zhang, Yibing Lv, and Yuzhen Guo. "ADMM-type methods for generalized multi-facility Weber problem." Journal of Industrial & Management Optimization 13, no. 5 (2017): 0. http://dx.doi.org/10.3934/jimo.2020171.

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Bell, Michelle L., Benjamin F. Hobbs, Emily M. Elliott, Hugh Ellis, and Zachary Robinson. "An evaluation of multi-criteria methods in integrated assessment of climate policy." Journal of Multi-Criteria Decision Analysis 10, no. 5 (September 2001): 229–56. http://dx.doi.org/10.1002/mcda.305.

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Chen, Xiao Yun, Xian Fu Chen, Shao Quan Zhang, and Wen Bin Zhang. "Classification Moving Vehicle Based on Multisensor Data Using Fusion of Multi-Class SVMs Methods." Advanced Materials Research 945-949 (June 2014): 1978–81. http://dx.doi.org/10.4028/www.scientific.net/amr.945-949.1978.

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In this paper, we propose a special Multi-class SVMs (MSVM) data fusion strategy which is applied to classify vehicle based on multiple pavement structural strain time histories. The centralized and distributed fusion strategies are applied to combine information from several data sources. In the centralized strategy, all information from several data sources is centralized and combined to construct an input space. Then a MSVM classifier is trained. In distributed schemes, the individual data sources are processed separately and modeled by using the MSVM. Then new data fusion strategies are used to combine the information from the individual MSVM to acquire the final classification outputs. Two popular Multi-class SVMs algorithms (One-against-all OAA, One-against-one OAO) are used to construct classifier based on aforementioned two fusion strategies, respectively. The results are compared between SVM-based fusion approach and single data source SVM using two MSVM algorithms, respectively. The result shows this SVM-based fusion approach significantly improves the results of classification accuracy and robustness. The proposed Multisensor data fusion methods can also be applied in other fields.

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Fraile, J. C., J. Perez-Turiel, J. L. Gonzalez-Sanchez, E. Baeyens, and R. Perez. "Comparative analysis of collision-free path-planning methods for multi-manipulator systems." Robotica 24, no. 6 (July 11, 2006): 711–26. http://dx.doi.org/10.1017/s0263574706002888.

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Motion planning for manipulators with many degrees of freedom is a complex task. The research in this area has been mostly restricted to static environments. This paper presents a comparative analysis of three reactive on-line path-planning methods for manipulators: the elastic-strip, strategy-based and potential field methods. Both the elastic-strip method [O. Brock and O. Khatib, “Elastic strips: A framework for integrated planning and execution,” Int. Symp. Exp. Robot. 245–254 (1999)] and the potential field method [O. Khatib, “Real-time obstacle avoidance for manipulators and mobile robots,” Int. J. Robot. Res.5(1), 90–98 (1986)] have been adapted by the authors to the problem at hand related to our multi-manipulator system (MMS) (three manipulators with five degrees of freedom each). Strategy-based method is an original contribution by the authors [M. Mediavilla, J. L. González, J. C. Fraile and J. R. Perán, “Reactive approach to on-line path planning for robot manipulators in dynamic environments,” Robotica20, 375–384 (2002); M. Mediavilla, J. C. Fraile, T. González and I. J. Galindo, “Selection of strategies for collision-free motion in multi-manipulator systems,” J. Intell. Robot Syst38, 85–104 (2003)].The three methods facilitate on-line path planning for our MMS in dynamic environments with collision avoidance, where the three manipulators may move at the same time in their common workspace. We have defined some ‘basic motion problems’ for the MMS, and a series of simulations has been running that will tell us how effective each path-planning method is. The simulations have been performed and the obtained results have been analysed by using a software program developed by the authors.The paper also presents experimental results obtained applying the path-planning methods to our MMS, that perform pick-and-place tasks sharing common working areas.

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Akram, Muhammad, and Shumaiza. "Multi-criteria decision-making methods based on q-rung picture fuzzy information." Journal of Intelligent & Fuzzy Systems 40, no. 5 (April 22, 2021): 10017–42. http://dx.doi.org/10.3233/jifs-202646.

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The q-rung picture fuzzy sets serve the fuzzy set theory as a competent, broader and accomplished extension of q-rung orthopair fuzzy sets and picture fuzzy sets which exhibit excellent performance in modeling the obscure data beyond the limits of existing approaches owing to the parameter q and three real valued membership functions. The accomplished strategy of VIKOR method is established on the major concepts of regret measure and group utility measure to specify the compromise solution. Further, TOPSIS method is another well established multi-criteria decision-making strategy that finds out the best solution with reference to the distances from ideal solutions. In this research study, we propose the innovative and modified versions of VIKOR and TOPSIS techniques using the numerous advantages of q-rung picture fuzzy information for obtaining the compromise results and rankings of alternatives in decision-making problems with the help of two different point-scales of linguistic variables. The procedure for the entropy weighting information is adopted to compute the normal weights of attributes. The q-rung picture fuzzy VIKOR (q-RPF VIKOR) method utilizes ascending order to rank the alternatives on the basis of maximum group utility and minimum individual regret of opponent. Moreover, a compromise solution is established by scrutinizing the acceptable advantage and the stability of decision. In the case of TOPSIS technique, the distances of alternatives to ideal solutions are determined by employing the Euclidean distance between q-rung picture fuzzy numbers. The TOPSIS method provides the ranking of alternatives by considering the descending order of closeness coefficients. For explanation, the presented methodologies are practiced to select the right housing society and the suitable industrial robot. The comparative results of the proposed techniques with four existing approaches are also presented to validate their accuracy and effectiveness.

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Dožić, Slavica. "Multi-criteria decision making methods: Application in the aviation industry." Journal of Air Transport Management 79 (August 2019): 101683. http://dx.doi.org/10.1016/j.jairtraman.2019.101683.

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Park, Jin Seok, and Chongam Kim. "Higher-order multi-dimensional limiting strategy for discontinuous Galerkin methods in compressible inviscid and viscous flows." Computers & Fluids 96 (June 2014): 377–96. http://dx.doi.org/10.1016/j.compfluid.2013.11.030.

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Vetschera, Rudolf. "Strategic Manipulation of Preference Information in Multi-Criteria Group Decision Methods." Group Decision and Negotiation 14, no. 5 (September 2005): 393–414. http://dx.doi.org/10.1007/s10726-005-8918-5.

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Xu, Wei Min, Bao Bao Ding, Rui Geng, and Xian Wen Zhou. "A Synchronous Control Strategy for Independent Multi-Motor System Based on CMAC." Advanced Materials Research 468-471 (February 2012): 115–21. http://dx.doi.org/10.4028/www.scientific.net/amr.468-471.115.

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With progress making in the art of industrial fields, control methods for synchronized multi-motor systems get more and more extensive applications, and there are increasingly high requirements for synchronous controllers. In this paper, a new control method for multi-axis drive systems is proposed, an adjacent-coupling algorithm based synchronization control strategy is designed, and a CMAC neural network based controller is developed. Simulation results show good performance of synchronization control accuracy, interference immunity, and convergence for the suggested synchronous controller

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Gao, Huina, Michael O. Ball, and Itir Z. Karaesmen. "Distribution-free methods for multi-period, single-leg booking control." Journal of Revenue and Pricing Management 15, no. 6 (December 2016): 425–53. http://dx.doi.org/10.1057/s41272-016-0063-z.

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LIU, ZIYING, SIEU PHAN, FAZEL FAMILI, YOULIAN PAN, ANNE E. G. LENFERINK, CHRISTIANE CANTIN, CATHERINE COLLINS, and MAUREEN D. O'CONNOR-MCCOURT. "A MULTI-STRATEGY APPROACH TO INFORMATIVE GENE IDENTIFICATION FROM GENE EXPRESSION DATA." Journal of Bioinformatics and Computational Biology 08, no. 01 (February 2010): 19–38. http://dx.doi.org/10.1142/s0219720010004495.

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An unsupervised multi-strategy approach has been developed to identify informative genes from high throughput genomic data. Several statistical methods have been used in the field to identify differentially expressed genes. Since different methods generate different lists of genes, it is very challenging to determine the most reliable gene list and the appropriate method. This paper presents a multi-strategy method, in which a combination of several data analysis techniques are applied to a given dataset and a confidence measure is established to select genes from the gene lists generated by these techniques to form the core of our final selection. The remainder of the genes that form the peripheral region are subject to exclusion or inclusion into the final selection. This paper demonstrates this methodology through its application to an in-house cancer genomics dataset and a public dataset. The results indicate that our method provides more reliable list of genes, which are validated using biological knowledge, biological experiments, and literature search. We further evaluated our multi-strategy method by consolidating two pairs of independent datasets, each pair is for the same disease, but generated by different labs using different platforms. The results showed that our method has produced far better results.

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Zhou, Feng, Zhiwu Huang, Weirong Liu, and Liran Li. "Formation Control with Event-Triggered Strategy for Multi-Agent Systems." Journal of Advanced Computational Intelligence and Intelligent Informatics 18, no. 1 (January 20, 2014): 71–77. http://dx.doi.org/10.20965/jaciii.2014.p0071.

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This paper considers cooperative formation control on networked multi-agent systems, in which the mobile agents have limited resources. Two event-based strategies are introduced to reduce resource utilization and control actuation in formation control. In one strategy, the event trigger function is designed to use system state, whereas in the other, it is designed to use control input. Theoretical and experimental analyses of the pros and cons of the two strategies are given. In addition, the stabilities of the two event-triggered formation control laws are discussed. The results of simulations conducted confirm the feasibility and effectiveness of the proposed methods.

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Iyogun, Paul. "Heuristic Methods for the Multi-Product Dynamic Lot Size Problem." Journal of the Operational Research Society 42, no. 10 (October 1991): 889. http://dx.doi.org/10.2307/2583416.

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Iyogun, Paul. "Heuristic Methods for the Multi-product Dynamic Lot Size Problem." Journal of the Operational Research Society 42, no. 10 (October 1991): 889–94. http://dx.doi.org/10.1057/jors.1991.169.

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Arcade, SH. "Single machine multi-product batch scheduling: Testing several solution methods." Omega 21, no. 6 (November 1993): 709–11. http://dx.doi.org/10.1016/0305-0483(93)90012-a.

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Wang, Yu Qing, Yu Xin Qin, Zhi Guo Li, and Le Deng. "Research on the Strategy of Multi Sensor Information Fusion in Coal Mine Disaster Scene." Applied Mechanics and Materials 220-223 (November 2012): 1929–33. http://dx.doi.org/10.4028/www.scientific.net/amm.220-223.1929.

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Different types of disasters occur frequently in coal mines. This paper analyzed the characteristics of different disasters, chosen the corresponding sensors to collect the information of disaster scene, and discussed the methods of multi sensor information fusion. Lastly, the multi-sensor information fusion strategies for fire, gas outburst, flood, and roof collapse were proposed in this research.

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Gurbuz, Feyza. "Strategy development with SWOT analysis on manufacturing companies in rapid growth: A ceramic industry application." New Trends and Issues Proceedings on Humanities and Social Sciences 4, no. 10 (January 12, 2018): 01–12. http://dx.doi.org/10.18844/prosoc.v4i10.3083.

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Decision-making is important for organisations, since the consequences of given decisions are identified among the major risk factors for organisations’ future. This study aims to prove the importance of using combined decision-making methods for a successful decision-making for managers. In a ceramics company, multi-criteria decision-making processes were applied for taking quick action for future strategies. SWOT analysis was used for determining potential strategies. After then, multicriteria decision-making methods were used to determine the importance of each potential strategy. Keywords: Multi-criteria decision-making, SWOT analysis, strategy management.

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D. Andricopoulos, Ari, Martin Widdicks, David P. Newton, and Peter W. Duck. "Extending quadrature methods to value multi-asset and complex path dependent options." Journal of Financial Economics 83, no. 2 (February 2007): 471–99. http://dx.doi.org/10.1016/j.jfineco.2005.10.009.

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Pradhan, Buddhadeb, Nirmal Baran Hui, Diptendu Sinha Roy, Gautam Srivastava, and Jerry Chun-Wei Lin. "Game-Theoretic Strategic Coordination and Navigation of Multiple Wheeled Robots." ACM Transactions on Internet Technology 21, no. 4 (July 16, 2021): 1–15. http://dx.doi.org/10.1145/3450521.

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Multiple robots negotiating in a dynamic workspace may lead to collisions. To avoid such issues, multi-robot navigation and coordination becomes necessary but is computationally very challenging, particularly when there are many robots. This article addresses the problem of multi-robot navigation where individual robots require coordination. Although a few such attempts for modeling multi-robot coordination and navigation have been studied, this work proposes a game-theoretic coordination strategy, also referred to as strategic coordination. We make use of a genetic algorithm tuned fuzzy logic–based motion planner. The proposed strategic coordination strategy has been pitted against a basic potential field-based motion planner, also referred to as the heuristic method, for performance comparison. Results are compared through computer simulation with 8 to 17 robots at different rounds. From the obtained results, it was observed that the proposed coordination scheme’s efficacy is strong for a larger number of robots. In addition, the proposed strategic coordination scheme with the genetic-fuzzy-based motion planner was found to outperform other combinations as far as the quality of solutions and time to reach the goal positions. The computational complexity of different methods has also been compared and presented.

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Khlevytska, T. B., and N. O. Plevako. "Scientific and Methodological Approach to Choosing the Financial Strategy of an Enterprise." PROBLEMS OF ECONOMY 4, no. 46 (2020): 241–48. http://dx.doi.org/10.32983/2222-0712-2020-4-241-248.

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The market transformation processes of Ukraine’s economy have determined the need for new approaches to managing the activities of domestic enterprises, ensuring their financial stability and competitiveness, especially when facing difficulties both in generating their own financial resources and raising funds from outside. Under such conditions, the issues of ensuring the strategic development of enterprises become especially relevant, requiring the search for optimum procedures of choosing such strategies, taking into account numerous criteria and alternatives. The purpose of the article is to substantiate a scientific and methodological approach to choosing a financial strategy for an enterprise, the choice being based on multi-vector and sound calculations. The approach is based on the hierarchy analysis method as one that helps to make decisions in complex, structured, multi-criteria and multi-alternative situations. The article substantiates the need for a profound analysis of the coordination of experts’ opinions, which would increase the argumentativeness and reasonableness of the strategy selection process. The expediency of extensively using mathematical methods while developing particular strategies and estimating the quality of their implementation is proven. The practical value of this approach lies in raising the validity level of the strategic decisions taken, and making it possible to provide their early and timely adjustment by differentiating criteria for decision-making and changing strategic alternatives. The proposed approach can be used to form a strategic portfolio for any enterprise, regardless of its scope of activity and form of ownership. Its end result is seen in improving the quality of strategic management at domestic enterprises.

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Palevičius, Vytautas, Gražvydas Mykolas Paliulis, Juratė Venckauskaitė, and Boleslovas Vengrys. "EVALUATION OF THE REQUIREMENT FOR PASSENGER CAR PARKING SPACES USING MULTI-CRITERIA METHODS." Journal of Civil Engineering and Management 19, no. 1 (January 16, 2013): 49–58. http://dx.doi.org/10.3846/13923730.2012.727463.

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The present situation shows that the parking infrastructure in residential areas of Vilnius does not satisfy the existing level of motorization. Every evening people come home from work and end up parking cars on lawns, cycle and pedestrian paths, playgrounds, fire accesses and etc. In Lithuania, this problem emerged with the growing number of cars. There have been attempts to address parking shortage issues 20–30 years ago by building metal above-ground garages and underground car parks; but such solutions focused on existing burning needs alone. As a result, the current parking situation in residential areas is chaotic. This problem stems from the ineffectiveness of responsible institutions, which maintain the status quo. Consequently – as no car parking development projects are planned and implemented as well as no required statistical data is collected regarding conditions of car parking and etc. – people are forced to look for a solution by themselves, thus end up parking on lawns or playgrounds. This article aims to apply multi-criteria solutions (Multiple Criteria Decision Making – MCDM), which would allow indicating the worst passenger car parking conditions in residential areas from the social, economic and environmental points of view. Besides, it pursues identifying and substantiating the choice of territories that require the development of car parking solutions.

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Ozcan-Deniz, Gulbin, and Yimin Zhu. "A MULTI-OBJECTIVE DECISION-SUPPORT MODEL FOR SELECTING ENVIRONMENTALLY CONSCIOUS HIGHWAY CONSTRUCTION METHODS." Journal of Civil Engineering and Management 21, no. 6 (June 9, 2015): 733–47. http://dx.doi.org/10.3846/13923730.2014.893915.

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The construction industry has a considerable share in overall resource and energy consumption. Consequently, decision-makers try to achieve environmentally conscious construction by integrating environmental objectives into the selection of construction elements. Due to the complexity of construction projects, it is a known challenge to provide an effective mechanism to select the most feasible construction methods. Thus, it is crucial to learn the interdependency between various resource alternatives, such as material and equipment type, under various project conditions like unavailability of resources. An analytic network process (ANP) was used in this study to construct a decision model for selecting the most feasible construction method. Data collected via interviews with highway construction experts were used to model the dependency between decision parameters, such as project conditions and resource performance indicators. The proposed ANP model output the relative importance weights of decision parameters so that they can be used to identify environmentally conscious construction methods. The proposed mechanism is a valuable asset for construction decision-makers especially when their ability to select construction methods is limited by project constraints. Although the model was tested in a highway project in this paper, it can be further extended to benefit building construction and sustainable decision-making problems.

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Morkūnaitė, Žydrūnė, Darius Kalibatas, and Diana Kalibatienė. "A BIBLIOMETRIC DATA ANALYSIS OF MULTI-CRITERIA DECISION MAKING METHODS IN HERITAGE BUILDINGS." JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT 25, no. 2 (February 8, 2019): 76–99. http://dx.doi.org/10.3846/jcem.2019.8315.

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Numerous countries are trying to find the best solution for conservation, restoration or reuse of the heritage buildings, preserving their cultural, historical, ethnic and spiritual values. The scientists, researchers and government are analysing the problems concerning with heritage building’s, like seismic issues, energy saving, sustainability, structures, materials and adaptive reuse. Since, heritage buildings’ reuse and preservation are characterized by multiple criteria, a multi-criteria decision making (MCDM) methods are useful in finding rational solutions for the previously mentioned problems. The current paper aims to overview papers on the MCDM approaches application in regard to heritage buildings’ reuse and preservation area. This study employs a bibliometric data analysis to explore state-of-the-art of the defined topic and an in-deep analysis – to synthesize the knowledge domain and critically evaluate a thorough literature in the analysed topic. As a result, scientific maps were created to reveal the knowledge domain of MCDM approaches in heritage buildings’ reuse and preservation. Finally, research gaps and future research directions are identified. Results of the analysis shows that till now MCDM approaches are not widely used in solving heritage buildings reuse and preservation issues. Moreover, there is luck of complex problem solving approach in cultural heritage buildings area.

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Willis, C. D., J. K. Greene, A. Abramowicz, and B. L. Riley. "Strengthening the evidence and action on multi-sectoral partnerships in public health: an action research initiative." Health Promotion and Chronic Disease Prevention in Canada 36, no. 6 (June 2016): 101–11. http://dx.doi.org/10.24095/hpcdp.36.6.01.

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Introduction The Public Health Agency of Canada’s Multi-sectoral Partnerships Initiative, administered by the Centre for Chronic Disease Prevention (CCDP), brings together diverse partners to design, implement and advance innovative approaches for improving population health. This article describes the development and initial priorities of an action research project (a learning and improvement strategy) that aims to facilitate continuous improvement of the CCDP’s partnership initiative and contribute to the evidence on multi-sectoral partnerships. Methods The learning and improvement strategy for the CCDP’s multi-sectoral partnership initiative was informed by (1) consultations with CCDP staff and senior management, and (2) a review of conceptual frameworks to do with multi-sectoral partnerships. Consultations explored the development of the multi-sectoral initiative, barriers and facilitators to success, and markers of effectiveness. Published and grey literature was reviewed using a systematic search strategy with findings synthesized using a narrative approach. Results Consultations and the review highlighted the importance of understanding partnership impacts, developing a shared vision, implementing a shared measurement system and creating opportunities for knowledge exchange. With that in mind, we propose a six-component learning and improvement strategy that involves (1) prioritizing learning needs, (2) mapping needs to evidence, (3) using relevant datacollection methods, (4) analyzing and synthesizing data, (5) feeding data back to CCDP staff and teams and (6) taking action. Initial learning needs include investigating partnership reach and the unanticipated effects of multi-sectoral partnerships for individuals, groups, organizations or communities. Conclusion While the CCDP is the primary audience for the learning and improvement strategy, it may prove useful for a range of audiences, including other government departments and external organizations interested in capturing and sharing new knowledge generated from multi-sectoral partnerships.

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Serafino, Aldo, Benoit Obert, and Paola Cinnella. "Multi-Fidelity Gradient-Based Strategy for Robust Optimization in Computational Fluid Dynamics." Algorithms 13, no. 10 (September 30, 2020): 248. http://dx.doi.org/10.3390/a13100248.

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Efficient Robust Design Optimization (RDO) strategies coupling a parsimonious uncertainty quantification (UQ) method with a surrogate-based multi-objective genetic algorithm (SMOGA) are investigated for a test problem in computational fluid dynamics (CFD), namely the inverse robust design of an expansion nozzle. The low-order statistics (mean and variance) of the stochastic cost function are computed through either a gradient-enhanced kriging (GEK) surrogate or through the less expensive, lower fidelity, first-order method of moments (MoM). Both the continuous (non-intrusive) and discrete (intrusive) adjoint methods are evaluated for computing the gradients required for GEK and MoM. In all cases, the results are assessed against a reference kriging UQ surrogate not using gradient information. Subsequently, the GEK and MoM UQ solvers are fused together to build a multi-fidelity surrogate with adaptive infill enrichment for the SMOGA optimizer. The resulting hybrid multi-fidelity SMOGA RDO strategy ensures a good tradeoff between cost and accuracy, thus representing an efficient approach for complex RDO problems.

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Liu, Xiaoli. "Research on decision-making strategy of soccer robot based on multi-agent reinforcement learning." International Journal of Advanced Robotic Systems 17, no. 3 (May 1, 2020): 172988142091696. http://dx.doi.org/10.1177/1729881420916960.

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This article studies a multi-agent reinforcement learning algorithm based on agent action prediction. In multi-agent system, the action of learning agent selection is inevitably affected by the action of other agents, so the reinforcement learning system needs to consider the joint state and joint action of multi-agent based on this. In addition, the application of this method in the cooperative strategy learning of soccer robot is studied, so that the multi-agent system can pass through the environment. To realize the division of labour and cooperation of multi-robots, the interactive learning is used to master the behaviour strategy. Combined with the characteristics of decision-making of soccer robot, this article analyses the role transformation and experience sharing of multi-agent reinforcement learning, and applies it to the local attack strategy of soccer robot, uses this algorithm to learn the action selection strategy of the main robot in the team, and uses Matlab platform for simulation verification. The experimental results prove the effectiveness of the research method, and the superiority of the proposed method is validated compared with some simple methods.

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Liang, Haoxiang, Huansheng Song, Huaiyu Li, and Zhe Dai. "Vehicle Counting System using Deep Learning and Multi-Object Tracking Methods." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 4 (March 16, 2020): 114–28. http://dx.doi.org/10.1177/0361198120912742.

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Using deep learning technology and multi-object tracking method to count vehicles accurately in different traffic conditions is a hot research topic in the field of intelligent transportation. In this paper, first, a vehicle dataset from the perspective of highway surveillance cameras is constructed, and the vehicle detection model is obtained by training using the You Only Look Once (YOLO) version 3 network. Second, an improved multi-scale and multi-feature tracking algorithm based on a kernel correlation filter (KCF) algorithm is proposed to avoid the KCF extracting single features and single-scale defects. Combining the intersection over union (IoU) similarity measure and the row-column optimal association criterion proposed in this paper, matching strategy is used to process the vehicles that are not detected and wrongly detected, thereby obtaining complete vehicle trajectories. Finally, according to the trajectory of the vehicle, the traveling direction of the vehicle is automatically determined, and the setting position of the detecting line is automatically updated to obtain the vehicle count result accurately. Experiments were conducted in a variety of traffic scenes and compared with published data. The experimental results show that the proposed method achieves high accuracy of vehicle detection while maintaining accuracy and precision in tracking multiple objects, and obtains accurate vehicle counting results which can meet real-time processing requirements. The algorithm presented in this paper has practical application for vehicle counting in complex highway scenes.

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Nalitolela, N. G., and H. Kadete. "Development of a Genetic Algorithm Based Search Strategy Suited For Design Optimisation of Internal Combustion Engines." Tanzania Journal of Engineering and Technology 31, no. 1 (June 30, 2008): 127–38. http://dx.doi.org/10.52339/tjet.v31i1.424.

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Engine design optimisation is a multi-objective, multi-domain problem in a discontinuous design space. The state of the art of optimisation techniques shows that only methods of direct and adaptive search are appropriate for this type of problem. These include, adaptive random search, simulated annealing, evolution strategies and genetic algorithms. Ofthese methods, the genetic algorithms have been shown to be the most suited for the optimisation of multi-modal response functions in a discontinuous design space. This paper considers the important characteristics of genetic algorithms and their adaptation for use in parametric design optimisation of internal combustion engines. In order to verify the basicfunctionality of the proposed optimisation strategy, a genetic algorithm based, optimisation software was developed and tested on a number of analytical functions, selected from optimisation literature, with satisfactory results.

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Su, Z., W. Dorigo, D. Fernández-Prieto, M. Van Helvoirt, K. Hungershoefer, R. de Jeu, R. Parinussa, et al. "Earth observation Water Cycle Multi-Mission Observation Strategy (WACMOS)." Hydrology and Earth System Sciences Discussions 7, no. 5 (October 11, 2010): 7899–956. http://dx.doi.org/10.5194/hessd-7-7899-2010.

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Abstract. Observing and monitoring the different components of the global water cycle and their dynamics are essential steps to understand the climate of the Earth, forecast the weather, predict natural disasters like floods and droughts, and improve water resources management. Earth observation technology is a unique tool to provide a global understanding of many of the essential variables governing the water cycle and monitor their evolution over time from global to basin scales. In the coming years an increasing number of Earth observation missions will provide an unprecedented capacity to quantify several of these variables on a routine basis. In this context, the European Space Agency (ESA), in collaboration with the Global Energy and Water Cycle Experiment (GEWEX) of the World Climate Research Program (WCRP), launched the Water Cycle Multi-Mission Observation Strategy (WACMOS) project in 2009. The project aims at developing and validating a novel set of geo-information products relevant to the water cycle covering the following thematic areas: evapotranspiration, soil moisture, cloud characterization and water vapour. The generation of these products is based on a number of innovative techniques and methods aiming at exploiting the synergies of different types of Earth observation data available today to the science community. This paper provides an overview of the major findings of the project with the ultimate goal of demonstrating the potential of innovative multi-mission based strategies to improve current observations by maximizing the synergistic use of the different types of information provided by the currently available observation systems.

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Copot, Cosmin, Clara Ionescu, Steve Vanlanduit, and Robin De Keyser. "Vibration suppression in multi-body systems by means of disturbance filter design methods." Journal of Vibration and Control 24, no. 14 (October 26, 2017): 2957–69. http://dx.doi.org/10.1177/1077546317736190.

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This paper addresses the problem of interaction in mechanical multi-body systems and shows that subsystem interaction can be considerably minimized while increasing performance if an efficient disturbance model is used. In order to illustrate the advantage of the proposed intelligent disturbance filter, two linear model based techniques are considered: IMC and the model based predictive (MPC) approach. As an illustrative example, multivariable mass-spring-damper and quarter car systems are presented. An adaptation mechanism is introduced to account for linear parameter varying LPV conditions. In this paper we show that, even if the IMC control strategy was not designed for MIMO systems, if a proper filter is used, IMC can successfully deal with disturbance rejection in a multivariable system, and the results obtained are comparable with those obtained by a MIMO predictive control approach. The results suggest that both methods perform equally well, with similar numerical complexity and implementation effort.

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Nell, Martin, Alexander Kubin, and Kay Hameyer. "Multi-Stage Optimization of Induction Machines Using Methods for Model and Parameter Selection." Energies 14, no. 17 (September 4, 2021): 5537. http://dx.doi.org/10.3390/en14175537.

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Optimization methods are increasingly used for the design process of electrical machines. The quality of the optimization result and the necessary simulation effort depend on the optimization methods, machine models and optimization parameters used. This paper presents a multi-stage optimization environment for the design optimization of induction machines. It uses the strategies of simulated annealing, evolution strategy and pattern search. Artificial neural networks are used to reduce the solution effort of the optimization. The selection of the electromagnetic machine model is made in each optimization stage using a methodical model selection approach. The selection of the optimization parameters is realized by a methodical parameter selection approach. The optimization environment is applied on the basis of an optimization for the design of an electric traction machine using the example of an induction machine and its suitability for the design of a machine is verified by a comparison with a reference machine.

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