TY  - CONF
SN  - 1062922X
PB  - Institute of Electrical and Electronics Engineers Inc.
EP  - 3125
AV  - none
N1  - 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
SP  - 3120
TI  - A multi-objective evolutionary approach for fuzzy optimization in production planning
Y1  - 2006///
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-34548125785&doi=10.1109%2fICSMC.2006.384595&partnerID=40&md5=ef869c3dd11f03eababb591c81716c55
A1  - Jiménez, F.
A1  - Sánchez, G.
A1  - Vasant, P.
A1  - Verdegay, J.L.
VL  - 4
CY  - Taipei
N2  - 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.
KW  - Decision making; Evolutionary algorithms; Fuzzy sets; Sensitivity analysis
KW  -  Multiple non dominated solutions; Product mix decision; Production planning
KW  -  Multi agent systems
ID  - scholars119
ER  -