Applying Iterated Local Search to the Permutation Flow Shop Problem
نویسنده
چکیده
Iterated local search (ILS) is a general and powerful metaheuristic which provides an easily implementable way of improving the performance of local search algorithms. In this article we consider the application of ILS to the permutation flow shop problem (FSP), a strongly studied problem in machine scheduling. We experimentally investigate the effect of specific implementation choices in our ILS algorithm and analyze its performance. Computational results show that our ILS approach compares very favorably to other approaches proposed for the FSP and is, despite its simplicity, even able to find new best solutions for some benchmark instances which have already been attacked by many other algorithms.
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