A Gravitational Emulation Local Search Algorithm for Task Scheduling in Multi-Agent System
One of the challenges in designing Multi-Agent Systems (MAS) on agents is breaking a job into several tasks and scheduling them among agents so that execution time is reduced and energy consumption become optimized as well load balancing is considered as a major factor on performance. On the other hands, one of the decisive factors in task scheduling and load balancing among agents is how to deploy tasks on agents. In this paper, a novel method is proposed based on a Gravitational Emulation Local search (GELS) algorithm for task scheduling among agents and load balancing. The performance of the proposed algorithm is evaluated in comparison with different sized test problems. Finally, simulation results show that proposed algorithm can solve the problem perfectly.
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