Integrated Iterated Local Search for the Permutation Flowshop Problem with Tardiness Minimization

In this paper, IILS (Integrated Iterated Local Search) is proposed for the permutation flow shop scheduling problem with the total tardiness minimization. Local searches are performed on an initial solution generated by NEHEDD. Insertion and swapping neighborhood structures are constructed, based on which an integrated neighborhood structure is investigated. In terms of the integrated neighborhood structure, the local search exploits the search space with strong intensification. To increase the diversification of IILS, a composite perturbation procedure is introduced, which performs either an insertion or swapping perturbation operation with a probability. The perturbation procedure is utilized to generate a candidate list of new start points for the next iteration of local searches. The new start point is selected according to a defined criterion, which takes into account both the distance factor and the objective function difference factor. Experimental results show that the proposed algorithm outperforms three existing best sequential meta-heuristics for the considered problem on most of the 60 benchmark instances in effectiveness with the same computation time limitation.