A GRASP-Simulated Annealing approach applied to solve Multi-Processor Task Scheduling problems

Task scheduling in Parallel processing systems is considered as one of the most difficult NP-hard optimization problems, it represents the most critical issue in managing multiprocessors. The greatest challenge in these problems is to find the best schedule for these tasks in a reasonable amount of time. This paper introduces a new hybrid metaheuristic algorithm called GRASP-Simulated annealing (GRASP-SA) to handle such problems. In this proposal, GRASP algorithm is modified by adopting Simulated Annealing procedure instead of classical local search procedure used in GRASP. This means, Improving the classical GRASP through adding more capabilities to escape local optima. To identify the influence of the proposed modifications, GRASP-SA is verified against the original GRASP, the original Simulated Annealing (SA), and the recently developed GRASP-GA. a set of benchmark problems are adopted in this experiment. The results indicate the proposed GRASP-SA has two-fold superiority over its competitors, it can achieve the schedule with the minimum make span through the minimum running time for most test problems.