Stochastic algorithms: Using the worst to reach the best

This research concerns permutation Flow Shop scheduling (in this case, a schedule is a total order on the jobs). In Flow-Shop problems, stochastic algorithms have been largely used to minimize the makespan or the total completion time. Usually, initial solutions are computed from heuristics. This paper shows that for stochastic algorithms, better results can be obtained by first looking at the worst solution (maximizing the criteria) then reversing the sequence and finally using this reverse solution as an initial solution. The quality of the results is improved for the makespan and the total completion time. The repeatability of the stochastic algorithm is also largely improved. It therefore appears that looking for the worst solution can be efficient in the search of the best.