Fuzzy Optimization via Multi-Objective Evolutionary Computation for Chocolate Manufacturing

Fernando Jiménez, Gracia Sánchez, Pandian Vasant and José Luis Verdegay
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Fernando Jiménez: University of Murcia
Gracia Sánchez: University of Murcia
Pandian Vasant: Universiti Teknologi Petronas
José Luis Verdegay: University of Granada

A chapter in Fuzzy Multi-Criteria Decision Making, 2008, pp 523-537 from Springer

Abstract: Abstract This chapter outlines, first, a real-world industrial problem for product mix selection involving 8 variables and 21 constraints with fuzzy coefficients and, second, a multi-objective optimization approach to solve the problem. This problem occurs in production planning in which a decision maker plays a pivotal role in making decisions under a fuzzy environment. Decision maker should be aware of his/her level-of-satisfaction as well as degree of fuzziness while making the product mix decision. Thus, the authors have analyzed using a modified S-curve membership function for the fuzziness patterns and fuzzy sensitivity of the solution found from the multi-objective optimization methodology. An ad hoc Pareto-based multi-objective evolutionary algorithm is proposed to capture multiple nondominated solutions in a single run of the algorithm. Results obtained have been compared with the well-known multi-objective evolutionary algorithm NSGA-II.

Keywords: Multi-objective optimization; evolutionary algorithm; NSGA-II (search for similar items in EconPapers)
Date: 2008
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-0-387-76813-7_20

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DOI: 10.1007/978-0-387-76813-7_20

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