Study on iterated local search algorithm for permutation flowshop problem with total flowtime objective

Abstract

Iterated Local Search (ILS) is a simple and efficient algorithm, which has been used to solve many combinatorial optimization problems. However, the effect of different search sequences in the local search procedure has not been studied. In this work, we used the ILS algorithm to solve the permutation flowshop scheduling problem with total flowtime objective, and observe the effect of different search sequences on this problem. Experimental results on benchmarks show that the search sequence does have some effect, though sometimes the effect may be little. If the iteration number is not so large, then the performance is better by changing the search sequence to the best solution found in the search process when the search process is trapped into local optimum. If the iteration number is rather large, then the performance is better by changing the search sequence to the best solution found in the search process immediately. Comparisons on benchmarks also show that ILS is comparable to the state of the art metaheuristics. © 2011 Springer-Verlag.