relation: https://khub.utp.edu.my/scholars/3577/
title: A multi-objective evolutionary approach for fuzzy optimization in production planning
creator: Jiménez, F.
creator: Sánchez, G.
creator: Vasant, P.
description: In this paper we propose a multi-objective optimization approach to solve nonlinear fuzzy optimization problems. Solutions in the Pareto front correspond with the fuzzy solution of the former fuzzy problem expressed in terms of the group of three parameters (x*, μ, α), i.e., optimal solution - degree of satisfaction - vagueness factor. The decision maker could choose, in a posteriori decision environment, the most convenient optimal solution according to his degree of satisfaction and vagueness factor. Additionally, an ad-hoc Pareto-based multi-objective evolutionary algorithm, ENORA-II, is proposed and validated in a production planning optimization environment. A real-world industrial problem for product-mix selection involving 8 decision variables and 21 constraints with fuzzy coefficients is considered as case study. ENORA-II has been evaluated with the existing methodologies in the field and results have been compared with the well-known multi-objective evolutionary algorithm NSGA-II. © 2013 - IOS Press and the authors. All rights reserved.
date: 2013
type: Article
type: PeerReviewed
identifier:   Jiménez, F. and Sánchez, G. and Vasant, P.  (2013) A multi-objective evolutionary approach for fuzzy optimization in production planning.  Journal of Intelligent and Fuzzy Systems, 25 (2).  pp. 441-455.  ISSN 10641246     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84878881939&doi=10.3233%2fIFS-130651&partnerID=40&md5=194d36dcf69eb9f1de25d17730a26dd4
relation: 10.3233/IFS-130651
identifier: 10.3233/IFS-130651