A DE-based approach to no-wait flow-shop scheduling

Abstract

This paper proposes an effective hybrid differential evolution (HDE) for the no-wait flow-shop scheduling problem (FSSP) with the makespan criterion, which is a typical NP-hard combinational optimization problem. Firstly, a largest-order-value (LOV) rule is presented to transform individuals in DE from real vectors to job permutations so that the DE can be applied for solving FSSPs. Secondly, the DE-based parallel evolution mechanism and framework is applied to perform effective exploration, and a simple but efficient local search developed according to the landscape of FSSP is applied to emphasize problem-dependent local exploitation. Thirdly, a speed-up evaluation method and a fast Insert-based neighborhood examining method are developed based on the properties of the no-wait FSSPs. Due to the hybridization of DE-based evolutionary search and problem-dependent local search as well as the utilization of the speed-up evaluation and fast neighborhood examining, the no-wait FSSPs can be solved efficiently and effectively. Simulations and comparisons based on well-known benchmarks demonstrate the efficiency, effectiveness, and robustness of the proposed HDE.