Ant Colony Optimization Inspired Swarm Optimization for Grid Task Scheduling

Metaheuristic algorithm is efficient for solving NP-complete problems such as scheduling. An algorithm called the exploration control particle swarm optimization (ECPSO) is proposed to solve grid task scheduling; a new velocity update rule on the basis of exploration capability is suggested; an exploration control probability (ECP) parameter is designed to control the search behaviour of particles to improve search efficiency. Meanwhile, a novel local search is also suggested for further improving the search efficiency. The proposed scheme has advantages of exploration preserving during search, complexity and computation time reduced and easy implementation. The experimental results indicate that the ECPSO proposed can effectively solve grid task scheduling problems.