Hybrid Differential Evolution Optimization for No-Wait Flow-Shop Scheduling with Sequence-Dependent Setup Times and Release Dates

• Published in: Advanced Intelligent Computing pp. 600 - 611
• Main Authors: Qian, Bin, Zhou, Hua-Bin, Hu, Rong, Xiang, Feng-Hong
• Format: Book Chapter
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg
• Series: Lecture Notes in Computer Science
• Subjects: differential evolution; local search; no-wait flow-shop scheduling; release dates; sequence-dependent setup times; speed-up evaluation
• ISBN: 364224727X; 9783642247279
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-642-24728-6_81

In this paper, a hybrid algorithm based on differential evolution (DE), namely HDE, is proposed to minimize the total completion time criterion of the no-wait flow-shop scheduling problem (NFSSP) with sequence-dependent setup times (SDSTs) and release dates (RDs), which is a typical NP-hard combinatorial optimization problem with strong engineering background. Firstly, to make DE suitable for solving flow-shop scheduling problem, a largest-order-value (LOV) rule is used to convert the continuous values of individuals in DE to job permutations. Secondly, a speed-up evaluation method is developed according to the property of the NFSSP with SDSTs and RDs. Thirdly, after the DE-based exploration, a problem-dependent local search is developed to emphasize exploitation. Due to the reasonable balance between DE-based global search and problem-dependent local search as well as the utilization of the speed-up evaluation, the NFSSP with SDSTs and RDs can be solved effectively and efficiently. Simulation results and comparisons demonstrate the superiority of HDE in terms of searching quality, robustness, and efficiency.