A hybrid intelligent system for multiobjective decision making problems

In attempt to solve multiobjective problems, many mathematical and stochastic methods have been developed. The methods operate based on the structured model of the problem. But most of the real-world problems are unstructured or semi-structured in objectives or constraints that caused lag of application of these traditional approaches in such problems. In this paper, a systematic design is introduced for such real multiobjective problems using hybrid intelligent system to cover ill-structured situations. Specially, fuzzy rule bases and neural networks are used in this systematic design and the developed hybrid system is established on noninferior region with the ability of mapping between objective space and solution space. The proof-of-principle results obtained on three test problems suggest that the proposed system can be extended to higher dimensional and more difficult multiobjective problems. A number of suggestions for extensions and application of the system is also discussed.