Pub Date : 2014-12-01DOI: 10.1109/MCDM.2014.7007206
H. V. Ayala, L. F. D. Cruz, R. Z. Freire, L. Coelho
By using biomechanical analyses applied to sports many researchers are providing important information to coaches and athletes in order to reach better performance in a shorter time. In swimming, these kinds of analyses are being used to evaluate, to detect and to improve the skills of high level athletes. Recently, evolutionary computing theories have been adopted to support swim velocity profile identification. Based on velocity profiles recognition, it is possible to identify distinct characteristics and classify swimmers according to their abilities. In this way, this work presents an application of Radial Basis Function Neural Network (RBF-NN) associated to a proposed cascaded evolutionary procedure composed by a genetic and Multiobjective Differential Evolution (MODE) algorithms as optimization method for searching the best fitness within a set of parameters to configure the RBF-NN. The main goal and novelty of the proposed approach is to enable, through the adoption of cascaded multiobjective optimization, the use of correlation based tests in order to select both the model lagged inputs and the associated parameters in a supervised fashion. Finally, the real data of a Brazilian elite female swimmer in crawl and breaststroke styles obtained into a 25 meters swimming pool have been identified by the proposed method. The soundness of the approach is illustrated with the adherence to the model validity tests and the values of the multiple correlation coefficients between 0.95 and 0.93 for two tests for both breaststroke and crawl strokes, respectively.
{"title":"Cascaded evolutionary multiobjective identification based on correlation function statistical tests for improving velocity analyzes in swimming","authors":"H. V. Ayala, L. F. D. Cruz, R. Z. Freire, L. Coelho","doi":"10.1109/MCDM.2014.7007206","DOIUrl":"https://doi.org/10.1109/MCDM.2014.7007206","url":null,"abstract":"By using biomechanical analyses applied to sports many researchers are providing important information to coaches and athletes in order to reach better performance in a shorter time. In swimming, these kinds of analyses are being used to evaluate, to detect and to improve the skills of high level athletes. Recently, evolutionary computing theories have been adopted to support swim velocity profile identification. Based on velocity profiles recognition, it is possible to identify distinct characteristics and classify swimmers according to their abilities. In this way, this work presents an application of Radial Basis Function Neural Network (RBF-NN) associated to a proposed cascaded evolutionary procedure composed by a genetic and Multiobjective Differential Evolution (MODE) algorithms as optimization method for searching the best fitness within a set of parameters to configure the RBF-NN. The main goal and novelty of the proposed approach is to enable, through the adoption of cascaded multiobjective optimization, the use of correlation based tests in order to select both the model lagged inputs and the associated parameters in a supervised fashion. Finally, the real data of a Brazilian elite female swimmer in crawl and breaststroke styles obtained into a 25 meters swimming pool have been identified by the proposed method. The soundness of the approach is illustrated with the adherence to the model validity tests and the values of the multiple correlation coefficients between 0.95 and 0.93 for two tests for both breaststroke and crawl strokes, respectively.","PeriodicalId":335170,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129686378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/MCDM.2014.7007193
Fei-Mei Wu, Dengfeng Li
The purpose of this paper is to develop a nonlinear programming method for solving a type of cooperative games in which there are multiple objectives and coalitions' values on objectives are expressed with intervals, which are called intervalvalued multiobjective cooperative games for short. In this method, we define the concepts of interval-valued cores of interval-valued multiobjective cooperative games and satisfactory degrees of comparing intervals with inclusion and/or overlap relations. The interval-valued cores can be computed by developing a new two-phase method based on the auxiliary nonlinear programming models. The proposed method can seek cooperative chances under the situations of inclusion and/or overlap relations of intervals in which the traditional interval ranking method may not always assure that the interval-valued cores exist. The feasibility and applicability of the developed method are illustrated with a real example.
{"title":"Nonlinear programming models and method for interval-valued multiobjective cooperative games","authors":"Fei-Mei Wu, Dengfeng Li","doi":"10.1109/MCDM.2014.7007193","DOIUrl":"https://doi.org/10.1109/MCDM.2014.7007193","url":null,"abstract":"The purpose of this paper is to develop a nonlinear programming method for solving a type of cooperative games in which there are multiple objectives and coalitions' values on objectives are expressed with intervals, which are called intervalvalued multiobjective cooperative games for short. In this method, we define the concepts of interval-valued cores of interval-valued multiobjective cooperative games and satisfactory degrees of comparing intervals with inclusion and/or overlap relations. The interval-valued cores can be computed by developing a new two-phase method based on the auxiliary nonlinear programming models. The proposed method can seek cooperative chances under the situations of inclusion and/or overlap relations of intervals in which the traditional interval ranking method may not always assure that the interval-valued cores exist. The feasibility and applicability of the developed method are illustrated with a real example.","PeriodicalId":335170,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125183527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/MCDM.2014.7007185
Eunice Oliveira, C. H. Antunes, Á. Gomes
A hybrid multi-objective approach based on GRASP (Greedy Randomized Adaptive Search Procedure) and SA (Simulated Annealing) meta-heuristics is proposed to provide decision support in a direct load control problem in electricity distribution networks. The main contributions of this paper are new techniques for the incorporation of preferences in these meta-heuristics and their hybridization. Preferences are included in the construction phase of multi-objective GRASP, in SA, as well as in the selection of solutions that go to the next generation, with the aim to obtain solutions more in accordance with the preferences elicited from a decision maker. The incorporation of preferences is made operational using the principles of the ELECTRE TRI method, which is based on the exploitation of an outranking relation in the framework of the sorting problem.
{"title":"A hybrid multi-objective GRASP+SA algorithm with incorporation of preferences","authors":"Eunice Oliveira, C. H. Antunes, Á. Gomes","doi":"10.1109/MCDM.2014.7007185","DOIUrl":"https://doi.org/10.1109/MCDM.2014.7007185","url":null,"abstract":"A hybrid multi-objective approach based on GRASP (Greedy Randomized Adaptive Search Procedure) and SA (Simulated Annealing) meta-heuristics is proposed to provide decision support in a direct load control problem in electricity distribution networks. The main contributions of this paper are new techniques for the incorporation of preferences in these meta-heuristics and their hybridization. Preferences are included in the construction phase of multi-objective GRASP, in SA, as well as in the selection of solutions that go to the next generation, with the aim to obtain solutions more in accordance with the preferences elicited from a decision maker. The incorporation of preferences is made operational using the principles of the ELECTRE TRI method, which is based on the exploitation of an outranking relation in the framework of the sorting problem.","PeriodicalId":335170,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123229030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/MCDM.2014.7007190
Zhichao Shi, Rui Wang, Zhang Tao
The preference-inspired co-evolutionary algorithm using goal vectors (PICEA-g) has been demonstrated to perform well on multi-objective problems. The superiority of PICEA-g originates from the smart fitness assignment, that is, candidate solutions are co-evolved with goal vectors along the search. In this study, we identify a limitation of this fitness assignment method, and propose an enhanced fitness assignment method which considers both the performance of goal vectors and the Pareto dominance rank on the fitness calculation of candidate solutions. Experimental results show that PICEA-g with the enhanced approach is effective, especially for bi-objective problems.
{"title":"PICEA-g using an enhanced fitness assignment method","authors":"Zhichao Shi, Rui Wang, Zhang Tao","doi":"10.1109/MCDM.2014.7007190","DOIUrl":"https://doi.org/10.1109/MCDM.2014.7007190","url":null,"abstract":"The preference-inspired co-evolutionary algorithm using goal vectors (PICEA-g) has been demonstrated to perform well on multi-objective problems. The superiority of PICEA-g originates from the smart fitness assignment, that is, candidate solutions are co-evolved with goal vectors along the search. In this study, we identify a limitation of this fitness assignment method, and propose an enhanced fitness assignment method which considers both the performance of goal vectors and the Pareto dominance rank on the fitness calculation of candidate solutions. Experimental results show that PICEA-g with the enhanced approach is effective, especially for bi-objective problems.","PeriodicalId":335170,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129760083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/MCDM.2014.7007191
Nandita Sen, Akash Ghosh, A. Saha, B. Karmaker
The evidence of UNDESA framework of sustainability assessment in MCDM paradigm is scarce generically and particularly, the status of sustainability of Indian states has never been assessed in accordance with UNDESA 2007 framework. This paper is an attempt to explore the paradigm of Multi-criteria Decision Making (MCDM) Methods in construction of sustainability index. To do so, we have used methods namely, Simple Additive Weighted Sum (SAWM), ELECTRE II, TOPSIS, PROMETHEE on the United Nations CSD indicators framework to evaluate the sustainability status of different states of India, which is among the fastest growing countries of todays world. We also try to understand the relative stability and distributional property of sustainability ranks obtained by different states. The ranks obtained by the different Methods are found to be relatively stable in comparative aspect. This implies that the choice of method does not make a big difference if the policy makers are interested for a group of entities to reward the superiors and support the laggards. On the other hand, a comprehensible and tractable method can be recommended for policy practice instead of less comprehensible one. Of course, use of a compendium of MCDM methods is always preferable for robustness analysis in decision-analytic aspect.
{"title":"Sustainability status of Indian states: Application and assessment of MCDM frameworks","authors":"Nandita Sen, Akash Ghosh, A. Saha, B. Karmaker","doi":"10.1109/MCDM.2014.7007191","DOIUrl":"https://doi.org/10.1109/MCDM.2014.7007191","url":null,"abstract":"The evidence of UNDESA framework of sustainability assessment in MCDM paradigm is scarce generically and particularly, the status of sustainability of Indian states has never been assessed in accordance with UNDESA 2007 framework. This paper is an attempt to explore the paradigm of Multi-criteria Decision Making (MCDM) Methods in construction of sustainability index. To do so, we have used methods namely, Simple Additive Weighted Sum (SAWM), ELECTRE II, TOPSIS, PROMETHEE on the United Nations CSD indicators framework to evaluate the sustainability status of different states of India, which is among the fastest growing countries of todays world. We also try to understand the relative stability and distributional property of sustainability ranks obtained by different states. The ranks obtained by the different Methods are found to be relatively stable in comparative aspect. This implies that the choice of method does not make a big difference if the policy makers are interested for a group of entities to reward the superiors and support the laggards. On the other hand, a comprehensible and tractable method can be recommended for policy practice instead of less comprehensible one. Of course, use of a compendium of MCDM methods is always preferable for robustness analysis in decision-analytic aspect.","PeriodicalId":335170,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131853768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/MCDM.2014.7007181
Bastien Rizzon, S. Galichet, V. Clivillé
It is well established that making decisions from defined data according to various criteria requires the use of MultiCriteria Decision Aiding or Analysis (MCDA) methods. However the necessary input data for these approaches are often ill-known especially when the data are a priori estimated. The common MCDA approaches consider these data as singular/scalar values. This paper deals with the consideration of more realistic, values by studying the impact of imprecision on a classical “precise” ranking established with ACUTA, a method based on additive utilities. We propose a generic approach to establish the concordance of pairwise relations of preference despite interval-based imprecision by complementing ACUTA with a computation of Kendall's index of concordance and of a threshold for maintaining this concordance. The methodology is applied to an industrial case subjected to Sustainable Development problems.
{"title":"Robustness threshold methodology for multicriteria based ranking using imprecise data","authors":"Bastien Rizzon, S. Galichet, V. Clivillé","doi":"10.1109/MCDM.2014.7007181","DOIUrl":"https://doi.org/10.1109/MCDM.2014.7007181","url":null,"abstract":"It is well established that making decisions from defined data according to various criteria requires the use of MultiCriteria Decision Aiding or Analysis (MCDA) methods. However the necessary input data for these approaches are often ill-known especially when the data are a priori estimated. The common MCDA approaches consider these data as singular/scalar values. This paper deals with the consideration of more realistic, values by studying the impact of imprecision on a classical “precise” ranking established with ACUTA, a method based on additive utilities. We propose a generic approach to establish the concordance of pairwise relations of preference despite interval-based imprecision by complementing ACUTA with a computation of Kendall's index of concordance and of a threshold for maintaining this concordance. The methodology is applied to an industrial case subjected to Sustainable Development problems.","PeriodicalId":335170,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126296008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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