Dependent-chance programming with fuzzy decisions

Dependent-chance programming (DCP) is a new type of stochastic programming and has been extended to the area of fuzzy programming, This paper provides a spectrum of DCP and dependent-chance multiobjective programming (DCMOP) as Hell as dependent-chance goal programming (DCGP) models with fuzzy rathe r than crisp decisions. The terms of uncertain environment, event, chance f unction, and induced constraints are discussed in the case of fuzzy decisio ns. A technique of fuzzy simulation is also designed for computing chance f unctions. Finally, we present a fuzzy simulation-based genetic algorithm Fo r solving these models and illustrate its effectiveness by some numerical e xamples.