relation: https://khub.utp.edu.my/scholars/487/
title: Fuzzy optimization via multi-objective evolutionary computation for chocolate manufacturing
creator: Jiménez, F.
creator: Sánchez, G.
creator: Vasant, P.
creator: Verdegay, J.L.
description: 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. © Springer Science + Business Media, LLC 2008.
publisher: Springer International Publishing
date: 2008
type: Article
type: PeerReviewed
identifier:   Jiménez, F. and Sánchez, G. and Vasant, P. and Verdegay, J.L.  (2008) Fuzzy optimization via multi-objective evolutionary computation for chocolate manufacturing.  Springer Optimization and Its Applications, 16.  pp. 523-537.  ISSN 19316828     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84976463510&doi=10.1007%2f978-0-387-76813-7_20&partnerID=40&md5=5e56809f2714715625edf5d2fdd156e2
relation: 10.1007/978-0-387-76813-7₂₀
identifier: 10.1007/978-0-387-76813-7₂₀