Task Scheduling Using Particle Swarm OptimizationAlgorithm with a Selection Guide and a Measure ofUniformity for Computational Grids

In this paper, we proposed an algorithm for solving the problem of taskscheduling using particle swarm optimization algorithm, With changes in theSelection and removing the guide and also using the technique to get away lrom thebad, to move away lrom local extreme and diversity. Scheduling algorithms play animportant role in grid computing, parallel tasks Scheduling and sending them toappropriate resources. The proposed method has less Makespan and price. Inaddition to implementing a grid computing system, the proposed method which isusing three standard test functions in evolutionary multi—objective optimimtion isevaluated. In this paper, the number of elements in the assessment of the Paretooptimizes set, uniformity and error. The results show that this Search method hasmore optimization in particle number density and high accuracy with less error thanthe MOPSO and can be replaced as an elfective solution for solving multi—objectiveoptimimtion

کلیدواژه ها:

Task scheduling ، load balancing ، multi—objective optimimtion ، particle swarmoptimization ، guide select ، guide remove ، Distance density