%X This paper outlines, first, a real-world industrial problem for product-mix selection involving 8 variables and 21 constraints with fuzzy coefficients and thereafter, 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 decision under 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 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 non dominated solutions in a single run of the algorithm. Results obtained have been compared with the well-known multi-objective evolutionary algorithm NSGA-II. © 2006 IEEE.
%K Decision making; Evolutionary algorithms; Fuzzy sets; Sensitivity analysis, Multiple non dominated solutions; Product mix decision; Production planning, Multi agent systems
%R 10.1109/ICSMC.2006.384595
%D 2006
%J Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
%L scholars119
%O cited By 18; Conference of 2006 IEEE International Conference on Systems, Man and Cybernetics ; Conference Date: 8 October 2006 Through 11 October 2006; Conference Code:70120
%C Taipei
%I Institute of Electrical and Electronics Engineers Inc.
%V 4
%A F. Jiménez
%A G. Sánchez
%A P. Vasant
%A J.L. Verdegay
%T A multi-objective evolutionary approach for fuzzy optimization in production planning
%P 3120-3125