Computers and Operations Research
A genetic algorithm for flowshop sequencing
Computers and Operations Research - Special issue on genetic algorithms
Parallel Path-Relinking Method for the Flow Shop Scheduling Problem
ICCS '08 Proceedings of the 8th international conference on Computational Science, Part I
Parallel scatter search algorithm for the flow shop sequencing problem
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
Parallel hybrid metaheuristics for the scheduling with fuzzy processing times
ICAISC'10 Proceedings of the 10th international conference on Artifical intelligence and soft computing: Part II
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In this paper we present two simulated annealing algorithms (sequential and parallel) for the permutation flow shop sequencing problem with the objective of minimizing the flowtime. We propose a neighbourhood using the so-called blocks of jobs on a critical path and specific accepting function. We also use the lower bound of cost function. By computer simulations on Taillard [17] and other random problems, it is shown that the performance of the proposed algorithms is comparable with the random heuristic technique discussed in literature. The proposed properties can be applied in any local search procedures.