Elephant Herding Optimization for Multiprocessor Task Scheduling in Heterogeneous Environment

In this study, a novel method has been implemented to solve the problems of task scheduling. This study observances the problem of dynamic multiprocessor task scheduling in a heterogeneous grid environment. Here, the scheduling problem of task is designed as an optimization problem. Recently developed swarm intelligence-based metaheuristic algorithm named, elephant herding optimization (EHO) has been implemented to minimize the makespan for task scheduling problem. EHO method is motivated by the herding performance of group of elephants. The simulation results verified that the implemented algorithm surpasses various other metaheuristic algorithms, such as shuffled frog leaping algorithm (SFLA), particle swarm optimization (PSO) and genetic algorithm (GA).