A hybrid artificial bee colony algorithm for the job shop scheduling problem

The job shop scheduling problem (JSSP) has attracted much attention in the field of both information sciences and operations research. In terms of the objective function, most existing research has been focused on the makespan criterion (i.e., minimizing the overall completion time). However, for contemporary manufacturing firms, the due date related performance is usually more important because it is crucial for maintaining a high service reputation. Therefore, in this study we aim at minimizing the total weighted tardiness in JSSP. Considering the high complexity, a novel artificial bee colony (ABC) algorithm is proposed for solving the problem. A neighborhood property of the problem is discovered, and then a tree search algorithm is devised to enhance the exploitation capability of ABC. According to extensive computational tests, the proposed approach is efficient in solving the job shop scheduling problem with total weighted tardiness criterion.