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

机译:改进的多目标粒子群优化算法用于服务工作流程调度

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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:服务工作流程中的时间成本优化问题是一种难以解决和广泛存在的实际系统问题。本文提出了一种改进的多目标PSO方法。通过构建离散颗粒,引入基于利基技术的基于利基技术的群体和啮合方法以获得均匀分布的帕累托集,实验结果表明,所提出的算法对于所考虑的问题是有效和有效的。为各种特征实例获得了具有高质量的许多均匀分布的Pareto组。

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