Fuzzy Simheuristics: Solving Optimization Problems under Stochastic and Uncertainty Scenarios

Diego Oliva, Pedro Copado, Salvador Hinojosa, Javier Panadero, Daniel Riera and Angel A. Juan
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Diego Oliva: IN3—Computer Science, Multimedia and Telecommunication Department, Universitat Oberta de Catalunya, 08018 Barcelona, Spain
Pedro Copado: IN3—Computer Science, Multimedia and Telecommunication Department, Universitat Oberta de Catalunya, 08018 Barcelona, Spain
Salvador Hinojosa: Departamento de Ciencias Computacionales, Universidad de Guadalajara, CUCEI, Guadalajara 44160, Mexico
Javier Panadero: IN3—Computer Science, Multimedia and Telecommunication Department, Universitat Oberta de Catalunya, 08018 Barcelona, Spain
Daniel Riera: IN3—Computer Science, Multimedia and Telecommunication Department, Universitat Oberta de Catalunya, 08018 Barcelona, Spain
Angel A. Juan: IN3—Computer Science, Multimedia and Telecommunication Department, Universitat Oberta de Catalunya, 08018 Barcelona, Spain

Mathematics, 2020, vol. 8, issue 12, 1-19

Abstract: Simheuristics combine metaheuristics with simulation in order to solve the optimization problems with stochastic elements. This paper introduces the concept of fuzzy simheuristics, which extends the simheuristics approach by making use of fuzzy techniques, thus allowing us to tackle optimization problems under a more general scenario, which includes uncertainty elements of both stochastic and non-stochastic nature. After reviewing the related work, the paper discusses, in detail, how the optimization, simulation, and fuzzy components can be efficiently integrated. In order to illustrate the potential of fuzzy simheuristics, we consider the team orienteering problem (TOP) under an uncertainty scenario, and perform a series of computational experiments. The obtained results show that our proposed approach is not only able to generate competitive solutions for the deterministic version of the TOP, but, more importantly, it can effectively solve more realistic TOP versions, including stochastic and other uncertainty elements.

Keywords: simulation-optimization; simheuristics; fuzzy techniques; uncertainty (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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