A hybrid computational intelligent system for multiobjective supplier selection problem

Mohammad Reza Gholamian, Seyyed Mohammad Taghi Fatemi Ghomi and Mehdi Ghazanfari

International Journal of Management and Decision Making, 2006, vol. 7, issue 2/3, 216-233

Abstract: Solving multiobjective management and engineering problems is generally a very difficult goal. In these kinds of problems, the objectives often conflict across a high-dimensional problem space and may also require existence of computational resources. The solution methods developed for this problem are generally evolutionary algorithms, as the subset of computational intelligence. In this study, combination of the kind of above-mentioned methods with other intelligent systems is introduced as a hybrid system. The system is constructed on fuzzy rule base along with neural networks and genetic algorithms and used for one of the most important multiobjective problems in market planning, which is the supplier selection problem. In addition, a numerical example is provided to clarify performance of developed hybrid systems. Finally some discussions and conclusions are arrived at and recommendations for future studies are made.

Keywords: multiobjective decision making; supplier selection; fuzzy rules; rule-based systems; genetic algorithms; neural networks; computational intelligence; intelligent systems; fuzzy logic. (search for similar items in EconPapers)
Date: 2006
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