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

Unrelated parallel machine scheduling problem with additional resource (UPMSPR) has been extensivelyconsidered; 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 extensiveapplications 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 solutionrepresentation is presented Evolution quality of population is evaluated and an adaptive onlooker bee phase isimplemented, in which multiple search operators including reduced variable neighborhood search (RVNS) areconstructed, the number of the used onlooker bees and search operator are dynamically determined. Historicaloptimization data and a new scout phase are also used. A number of experiments are conducted on 300instances from the literature. The computational results demonstrate that the new strategies are effective andAABC can provide better results than the algorithms from the literature