Project Management With Uncertain Task Times

In this paper, parallel simulated annealing with genetic enhancement algorithm (HSG) is presented and applied to permutation flow shop scheduling problem which has been proven to be NP -complete in the strong sense. The metaheuristics is based on a new clustering algorithm for simulated annealing but introduces a new mechanism for dynamic SA parameters adjustment based on genetic algorithms. The proposed parallel algorithm is based on the master-slave model with cooperation. Fuzzy arithmetic on fuzzy numbers is used to determine the minimum completion times C-max. Finally, the computation results and discussion of the algorithms performance are presented.