Metaheuristic approaches for multiprocessor scheduling

Abstract

In the multiprocessor scheduling problem, a given list of tasks has to be scheduled on identical parallel processors. Each task in the list is defined by a release date, a due date and a processing time. The objective is to minimize the number of processors used while respecting the constraints imposed by release dates and due dates. This objective is clearly linked with minimizing the cost of hardware needed for implementing a specific application. In this paper, we have proposed two metaheuristic approaches for this problem. The first approach is based on artificial bee colony algorithm, whereas the latter approach is based on invasive weed optimization algorithm. On the standard benchmark instances for the problem, performances of our approaches are comparable to other state-of-theart approaches.