The new concepts in parallel simulated annealing method

Abstract

New elements of the parallel simulated annealing method are proposed to solve the permutation flow shop scheduling problem with the criterion of total completion time (F*||Csum). This problem is more difficult to optimize than F*||Cmax (minimizing the makespan). Simulated annealing belongs to the artificial intelligence methods, which are commonly used to solve NP-hard combinatorial optimization problems. In the parallel algorithm, we propose a new acceptance probability function, multi-step technique, dynamic long-term memory and backtrack-jump. Computational experiments (for Taillard's benchmarks ta001-ta050, [8]) are given and compared with results yielded by the best algorithms discussed in literature [10]. We also present new referential solutions for ta051-ta080 instances (published on our benchmark page [1]), which so far have no solutions.