Fuzzy dynamic programming approach to hybrid multiobjective multistage decision-making problems

The purpose of this paper is to develop a new fuzzy dynamic programming approach for solving hybrid multiobjective multistage decision-making problems. We first present a methodology of fuzzy evaluation and fuzzy optimization for hybrid multiobjective systems, in which the qualitative and quantitative objectives are synthetically considered. The qualitative objectives are evaluated by decision-makers with linguistic variables and the quantitative objectives are converted into proper dimensionless indices. After getting the marginal evaluations for each objective, a new aggregation method based on the principle of fuzzy pattern recognition is developed to get a global evaluation for all objectives. With the global evaluation obtained, a fuzzy optimization process is performed. Then we present a dynamic optimization algorithm by incorporating the fuzzy optimization process with the conventional dynamic programming technique to solve hybrid multiobjective multistage decision-making problems. A characteristic feature of the approach proposed is that various objectives are synthetically considered by the fuzzy systematic technique instead of the frequently employed weighted average method. Finally, an illustrative example is also given to clarify the developed approach and to demonstrate its effectiveness.