Dependent-chance programming is a new type of stochastic programming. This paper provides a framework of dependent chance programming as well as dependent-chance multiobjective programming and dependent-chance goal programming in fuzzy environment as opposed to stochastic environment. We also extend the concepts of uncertain environments, events, chance functions and induced constraints from stochastic to fuzzy cases. Finally, a fuzzy simulation based genetic algorithm is instated by some numerical examples of dependent-chance programming models.
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