A hybrid artificial bee colony algorithm for the job-shop scheduling problem with no-wait constraint

• Published in: Soft computing (Berlin, Germany) Vol. 21; no. 5; pp. 1193 - 1202
• Main Authors: Sundar, Shyam, Suganthan, P. N., Jin, Chua Tay, Xiang, Cai Tian, Soon, Chong Chin
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2017; Springer Nature B.V
• Subjects: Artificial Intelligence; Bees; Computational Intelligence; Control; Engineering; Food; Foraging behavior; Genetic algorithms; Job shop scheduling; Mathematical Logic and Foundations; Mechatronics; Methodologies and Application; Optimization; Robotics; Scheduling; Search algorithms; Swarm intelligence; No-wait; Artificial bee colony algorithm; Scheduling; Swarm intelligence; Job-shop
• ISSN: 1432-7643; 1433-7479
• DOI: 10.1007/s00500-015-1852-9

This paper studies a hybrid artificial bee colony (ABC) algorithm for finding high quality solutions of the job-shop scheduling problem with no-wait constraint (JSPNW) with the objective of minimizing makespan among all the jobs. JSPNW is an extension of well-known job-shop scheduling problem subject to the constraint that no waiting time is allowed between operations for a given job. ABC algorithm is a swarm intelligence technique based on intelligent foraging behavior of honey bee swarm. The proposed hybrid approach effectively coordinates the various components of ABC algorithm such as solution initialization, selection and determination of a neighboring solution with the local search in such a way that it leads to high quality solutions for the JSPNW. The proposed approach is compared with the two best approaches in the literature on a set of benchmark instances. Computational results show the superiority of the proposed approach over these two best approaches.