Chemical-reaction optimization for flexible job-shop scheduling problems with maintenance activity

Abstract

This paper proposes an effective discrete chemical-reaction optimization (DCRO) algorithm for solving the flexible job-shop scheduling problems with maintenance activity constraints. Three minimization objectives—the maximum completion time (makespan), the total workload of machines and the workload of the critical machine are considered simultaneously. In the proposed algorithm, each solution is represented by a chemical molecule. Four improved elementary reactions, i.e., on-wall ineffective collision, inter-molecular ineffective collision, decomposition, and synthesis, are developed. A well-designed crossover function is introduced in the inter-molecular collision, synthesis, and decomposition operators. Tabu search (TS) based local search is embedded in DCRO to perform exploitation process. In addition, the decoding mechanism considering the maintenance activity is presented. Several neighboring approaches are developed to improve the local search ability of the DCRO. The proposed algorithm is tested on sets of the well-known benchmark instances. Through the analysis of experimental results, the highly effective performance of the proposed DCRO algorithm is shown against the best performing algorithms from the literature.