eprintid: 3577
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/35/77
datestamp: 2023-11-09 15:51:50
lastmod: 2023-11-09 15:51:50
status_changed: 2023-11-09 15:47:08
type: article
metadata_visibility: show
creators_name: Jiménez, F.
creators_name: Sánchez, G.
creators_name: Vasant, P.
title: A multi-objective evolutionary approach for fuzzy optimization in production planning
ispublished: pub
keywords: Degree of satisfaction; Fuzzy optimization; Multi objective evolutionary algorithms; Multi-objective evolutionary; NSGA-II; Optimization environments; Posteriori decision; Production Planning, Decision making; Evolutionary algorithms; Multiobjective optimization; Optimal systems; Pareto principle; Production control; Production engineering, Planning
note: cited By 41
abstract: 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
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84878881939&doi=10.3233%2fIFS-130651&partnerID=40&md5=194d36dcf69eb9f1de25d17730a26dd4
id_number: 10.3233/IFS-130651
full_text_status: none
publication: Journal of Intelligent and Fuzzy Systems
volume: 25
number: 2
pagerange: 441-455
refereed: TRUE
issn: 10641246
citation:   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