A Hybrid Particle Swarm Optimisation-genetic Algorithm Applied To Grid Scheduling

Scheduling problems have been thoroughly explored by the research community, but they acquire challenging characteristics in grid computing systems. In this context, it is important to have a scheduling strategy that can make efficient use of the available grid resources. This article focuses on the application of the particle swarm optimisation (PSO) meta-heuristic to the scheduling of independent users' jobs on grids. It is shown that the PSO method can achieve satisfactory results in simple problem instances, yet it has a tendency to stagnate around local minima in high-dimensional problems. Therefore, this research also proposes a novel hybrid particle swarm optimisation-genetic algorithm (H_PSO) method that aims to increase swarm diversity when a stagnation condition is detected. This new method is evaluated and compared with other heuristics and PSO formulations; the comparison shows that H_PSO can successfully improve the scheduling solution.7211312