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For realizing the more efficient scheduling of scientific workflow tasks,the multi—objective optimization prob— lem of workflow scheduling in cloud environment was researched and a workflow scheduling algorithm HPSO of hybrid particle swarm optimization based on non-dominance sort was presented.First,the mult._0bjective optimization model of workflow scheduling under budget and deadline constraint is established,which introduces three optimizaiton objec— fives,including the execution makespan of workflow,the execution cost and the execution energy consumption.Second, a hybrid particle swarm optimizaiton algorithm is designed to solve this three conflicting objectives optimization.Our al— gorithm can obtain the solutions set of workflow scheduling satisfying Pareto optimal by non-dominance sort.Finaly, through the simulation experiments of three types of scientific workflow case,we compared the proposed algorithm to the same types of multi—objective scheduling algorithms,such as NSGA-II,MOPSO and£一Fuzzy.The experimental re— sults show that the scheduling solution obtained by HPSO not noly has better convergence,but also has better uniform spacing distribution among the solutions,which can better accord with the workflow scheduling optimization in cloud

云环境中基于混合多目标粒子群的科学工作流调度算法 (Scientific Workflow Scheduling Algorithm Based on Hybrid Multi-objective Particle Swarm Optimization in Cloud Environment).