Multi-Objective Optimization Based on Genetic Algorithm in Grid Scheduling
Resources scheduling plays a vital role in Grid. This paper converts resources scheduling problem in Grid into a multi-objective optimization problem, and presents a resources scheduling approach based on multi-objective genetic algorithms. The authors propose the Genetic Algorithms (GA) for job scheduling on computational grids which optimizes the make span, flow time and also achieves effective utilization of resources. In this paper, they consider the allocations of jobs to resources using batch mode methods. Based on the computational results, they evaluate the performance of these methods with regard to the multi-objective parameters.