A discrete artificial bee colony algorithm incorporating differential evolution for the flow-shop scheduling problem with blocking

• Published in: Engineering optimization Vol. 47; no. 7; pp. 927 - 946
• Main Authors: Han, Yu-Yan, Gong, Dunwei, Sun, Xiaoyan
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 03.07.2015; Taylor & Francis Ltd
• Subjects: Algorithms; artificial bee colony; Blocking; Criteria; Design engineering; differential evolution; Evolution; flow-shop scheduling; Heuristic; Job shops; makespan; Operators; Optimization algorithms; Optimization techniques; Production scheduling; Scheduling; Searching; Swarm intelligence
• ISSN: 0305-215X; 1029-0273
• DOI: 10.1080/0305215X.2014.928817

A flow-shop scheduling problem with blocking has important applications in a variety of industrial systems but is underrepresented in the research literature. In this study, a novel discrete artificial bee colony (ABC) algorithm is presented to solve the above scheduling problem with a makespan criterion by incorporating the ABC with differential evolution (DE). The proposed algorithm (DE-ABC) contains three key operators. One is related to the employed bee operator (i.e. adopting mutation and crossover operators of discrete DE to generate solutions with good quality); the second is concerned with the onlooker bee operator, which modifies the selected solutions using insert or swap operators based on the self-adaptive strategy; and the last is for the local search, that is, the insert-neighbourhood-based local search with a small probability is adopted to improve the algorithm's capability in exploitation. The performance of the proposed DE-ABC algorithm is empirically evaluated by applying it to well-known benchmark problems. The experimental results show that the proposed algorithm is superior to the compared algorithms in minimizing the makespan criterion.