In this paper, we propose 260 scheduling problems whose size is greater than that of the rare examples published. Such sizes correspond to real dimensions of industrial problems.The types of problems that we propose are : the permutation flow shop, the job shop and the open shop scheduling problems.We restrict us to basic problems : the processing times are fixed, there are neither set-up times nor due dates nor release dates, etc. Then, the objective is the minimization of the makespan.

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We compare in this paper the best heuristic methods known up to now to solve the flow shop sequencing problem and we improve the complexity of the best one. Next, we apply to this problem taboo search, a new technique to solve combinatorial optimization problems, and we report computational experiments. Finally a parallel taboo search algorithm is presented and experimental results show that this heuristics allows very good speed-up.

This article presents a probabilistic technique to diversify, intensify, and parallelize a local search adapted for solving vehicle routing problems. This technique may be applied to a very wide variety of vehicle routing problems and local searches. It is shown that efficient first-level tabu searches for vehicle routing problems may be significantly improved with this technique. Moreover, the solutions produced by this technique may often be improved by a postoptimization technique presented in this article, too. The solutions of nearly forty problem instances of the literature have been improved,