This paper provides a spectrum of chance-constrained programming as well as
chance-constrained multiobjective programming and chance-constrained goal
programming with fuzzy rather than crisp decisions, which will seek a fuzzy
set from the given reference collection as an optimal solution. The techni
que of fuzzy simulation is also presented to check fuzzy chance constraints
and to handle fuzzy objective and goal constraints. Finally, a fuzzy simul
ation-based genetic algorithm for solving these models will be designed and
illustrated by some numerical examples. (C) 2001 Elsevier Science B.V. All
rights reserved.