A Hybrid Discrete Imperialist Competition Algorithm for Fuzzy Job-Shop Scheduling Problems - Wang, Shuaiqun; Aorigele; Liu, Guanjun; Gao, Shangce (IEEE Access, 2016)
Fuzzy job-shop scheduling problems (FJSPs) with various imprecise factors are a category of combination optimization problems known as non-deterministic polynomial-hard problems. In this paper, a hybrid algorithm HICATS combining discrete imperialist competition algorithm (ICA) and Tabu search (TS) is proposed to solve FJSPs with fuzzy processing time and fuzzy due date. The objective function is maximizing the minimum agreement index, which is on the basis of the agreement index of fuzzy due date and fuzzy completion time. In the proposed algorithm, ICA conducts the global search and TS performs the local search. The imperialist is used to guide the colonies in the same empire. So, local search approach based on TS is applied to the imperialist to perform fine-grained exploitation. The 6 × 6 and 10 × 10 FJSPs with fuzzy processing time and fuzzy due date are tested to evaluate the performance of the proposed algorithm HICATS in this paper. The highly effective performance of HICATS is shown against the best performing algorithms from the literature. Experimental results demonstrate the advantages of our proposed algorithm HICATS on the feasibility and robustness compared with other algorithms.