%0 Journal Article
%@ 19316828
%A Jiménez, F.
%A Sánchez, G.
%A Vasant, P.
%A Verdegay, J.L.
%D 2008
%F scholars:487
%I Springer International Publishing
%J Springer Optimization and Its Applications
%P 523-537
%R 10.1007/978-0-387-76813-7₂₀
%T Fuzzy optimization via multi-objective evolutionary computation for chocolate manufacturing
%U https://khub.utp.edu.my/scholars/487/
%V 16
%X 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.
%Z cited By 3