A New Dynamic Method of Multiprocessor Scheduling using Modified Crow Search Optimization

Abstract

The task scheduling problem in a heterogeneous multiprocessor system is a challenging area of research. This article proposes a population-based metaheuristic algorithm called Modified Crow Search Optimization (MCSO) algorithm to solve the task scheduling problem. In this paper, the task scheduling problem is considered an optimization problem. The MCSO algorithm is used to find out the minimum makespan and the speedup of the task scheduling problem. The proposed algorithm is compared with some standard algorithms like Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Shuffled Frog Leaping Algorithm (SFLA), and Crow Search Optimization (CSO). Experimental results prove that the proposed algorithm outperforms all the above algorithms in minimizing the makespan.