This study considers a novel class of hi-levelfuzzyrandomprogramming problems of insuring critical path. In this study, duration of each task is considered as a fuzzyrandom variable and follows the known possibili...
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This study considers a novel class of hi-levelfuzzyrandomprogramming problems of insuring critical path. In this study, duration of each task is considered as a fuzzyrandom variable and follows the known possibility and probability distributions. Because an effective way to directly solve the problem does not exist, we first reduce the chance constraint to two equivalent random subproblems under two different kinds of risk attitudes. Then, we use Sample Average Approximation (SAA) method for reformulating the equivalent randomprogramming subproblems as the approximation problems. Since the approximation problems are also difficult to solve, we explore a hybrid Genotype Phenotype binary Particle Swarm Optimization algorithm (GP-BPSO) for resolving two equivalent subproblems, in which Dynamic programming Method (DPM) is used for finding the solution in the lower-levelprogramming. At last, a series of simulation examples are provided for demonstrating the validity of the hybrid GP-BPSO compared with the hybrid BPSO algorithm. (C) 2018 Sharif University of Technology. All rights reserved.
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