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Improved multi-objective particle swarm optimization algorithm for service-workflows scheduling

机译:服务工作流调度的改进多目标粒子群优化算法

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Time-cost optimization problem in service-workflows is a hard to solve and widely existing problem in practical systems. In this paper, a improved multi-objective PSO method is proposed. By constructing discrete particles, Outside Population and Meshing method based on Niche Technique are introduced to obtain an evenly distributed Pareto set, Experimental results show that the proposed algorithm is effective and efficient for the considered problem. Many evenly distributed Pareto sets with high quality are obtained for various characteristic instances.
机译:服务工作流中的时间成本优化问题很难解决,并且在实际系统中广泛存在。本文提出了一种改进的多目标PSO方法。通过构造离散粒子,引入基于Niche技术的外部种群和网格划分方法,获得了均匀分布的帕累托集,实验结果表明,该算法对于所考虑的问题是有效的。对于各种特征实例,可以获得许多高质量的均匀分布的Pareto集。

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