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A multi-objective evolutionary approach for fuzzy optimization in production planning

P., Vasant and F., Jimenez and G., Sanchez and J.L., Verdegay (2007) A multi-objective evolutionary approach for fuzzy optimization in production planning. In: 2006 IEEE International Conference on Systems, Man and Cybernetics, 8 October 2006 through 11 October 2006, Taipei.

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Abstract

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.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:Decision making; Evolutionary algorithms; Fuzzy sets; Sensitivity analysis; Multiple non dominated solutions; Product mix decision; Production planning; Multi agent systems
Subjects:Q Science > Q Science (General)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments / MOR / COE:Departments > Computer Information Sciences
ID Code:136
Deposited By: Mr Helmi Iskandar Suito
Deposited On:02 Mar 2010 01:18
Last Modified:19 Jan 2017 08:27

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