Multiobjective Scheduling on Distributed Heterogeneous Computing and Grid Environments Using a Parallel Micro-CHC Evolutionary Algorithm

This work presents the application of a parallel micro-CHC evolutionary algorithm to the scheduling problem in heterogeneous computing environments, to minimize the make span and weighted response ratio objectives. The studied problem is NP-hard, and significant effort has been made to develop efficient methods to compute accurate schedules in reduced execution times. Efficient numerical results are reported in the experimental analysis performed on both well-known and new large problem instances that model medium-sized grid environments. The parallel micro-CHC achieves a high problem solving efficacy and shows a good scalability behavior when facing high dimension instances.