Multiprocessor Task Scheduling using a new Prioritizing Genetic Algorithm based on number of Task Children

Abstract

Due to optimal use of processors as well as spending less time, the task scheduling in multiprocessor systems is of great importance. This is one of the NP_hard problems and achieving the optimal schedule or finding the minimum schedule length, using the dynamic algorithm and back-tracking programming, would be time-consuming. Therefore, heuristic methods like genetic algorithms are suitable methods to schedule tasks in a multiprocessor system. In this paper, a new genetic algorithm is presented whose priority of tasks’ execution is based on the number of their children. The results show that our developed algorithm finds the near-optimal schedule in a reasonable computation time, compared to other heuristics.