A new hybrid Tabu-VNS metaheuristic for solving multiple objective scheduling problems

In the past several years, it has amply been demonstrated that metaheuristics, such as simulated annealing, tabu search, genetic algorithms and ant colony are simple, adaptable and computationally efficient to solve a large range of combinatorial problems including hard single objective industrial. In this paper, we propose a formalisation of the search process for finding compromise solutions using metaheuristics. To this end, the following section presents a generic approach incorporating compromise programming. We then develop a hybrid tabu search/variable neighbourhood search algorithm for solving a multiple objective scheduling problem. Our results indicate first that the tabu search approach adopted is an efficient means of finding single objective schedules, and then that it may be incorporated into the generic compromise programming approach.