An adaptive artificial bee colony for unrelated parallel machine scheduling with additional resource and maintenance

Abstract

Unrelated parallel machine scheduling problem with additional resource (UPMSPR) has been extensively considered; however, UPMSPR with preventive maintenance (PM) is seldom studied; on the other hand, artificial bee colony (ABC) has potential advantages on solving UPMSPR with PM because of the extensive applications of ABC to unrelated parallel machine scheduling. In this paper, an adaptive artificial bee colony (AABC) algorithm is proposed to solve UPMSPR with PM and makespan minimization. A new solution representation is presented Evolution quality of population is evaluated and an adaptive onlooker bee phase is implemented, in which multiple search operators including reduced variable neighborhood search (RVNS) are constructed, the number of the used onlooker bees and search operator are dynamically determined. Historical optimization data and a new scout phase are also used. A number of experiments are conducted on 300 instances from the literature. The computational results demonstrate that the new strategies are effective and AABC can provide better results than the algorithms from the literature.