A New Approach to Reducing Search Space and Increasing Efficiency in Simulation Optimization Problems via the Fuzzy-DEA-BCC | Zendy

Rafael de Carvalho Miranda | Zendy; José Arnaldo Barra Montevechi | Zendy; Aneirson Francisco da Silva | Zendy; Fernando Augusto Silva Marins | Zendy

Open Access

A New Approach to Reducing Search Space and Increasing Efficiency in Simulation Optimization Problems via the Fuzzy-DEA-BCC

Author(s) -

Rafael de Carvalho Miranda,

José Arnaldo Barra Montevechi,

Aneirson Francisco da Silva,

Fernando Augusto Silva Marins

Publication year - 2014

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2014/450367

Subject(s) - fuzzy logic , reliability (semiconductor) , data envelopment analysis , mathematical optimization , computer science , reduction (mathematics) , variable (mathematics) , computation , taguchi methods , discrete event simulation , simulation software , software , face (sociological concept) , mathematics , algorithm , artificial intelligence , simulation , machine learning , mathematical analysis , power (physics) , physics , geometry , quantum mechanics , programming language , social science , sociology

The development of discrete-event simulation software was one of the most successful interfaces in operational research with computation. As a result, research has been focused on the development of new methods and algorithms with the purpose of increasing simulation optimization efficiency and reliability. This study aims to define optimum variation intervals for each decision variable through a proposed approach which combines the data envelopment analysis with the Fuzzy logic (Fuzzy-DEA-BCC), seeking to improve the decision-making units' distinction in the face of uncertainty. In this study, Taguchi's orthogonal arrays were used to generate the necessary quantity of DMUs, and the output variables were generated by the simulation. Two study objects were utilized as examples of mono-andmultiobjective problems. Results confirmed the reliability and applicability of the proposed method, as it enabled a significant reduction in search space and computational demand when compared to conventional simulation optimization techniques

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