An iterated local search algorithm for distributed assembly permutation flowshop problem

Nowadays, the distributed assembly permutation flowshop problem (DAPFSP) has important applications in practice. In this paper, we propose a group iterated local search (gILS) algorithm to solve the problem with total flowtime (TF) criterion. We use the heuristic method based on a ascending order, which is originated from the NEH. In order to simplify and optimize the algorithm, we introduce two kinds of local search methods based on products and jobs respectively. In addition, considering the diversity of search area, we propose a probabilistic random selection based on the TF value and the number of iterations to determine the optimized solution. Acceptance criterion is a simple comparison to determine whether a new solution is acceptable or not. Finally, we calculate 180 instances with our proposed algorithm and compare the results with those from the recent effective algorithms. The results verify the superiority of the presented gILS algorithm.