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QoS-Aware Multiobjective Optimization Algorithm for Web Services Selection with Deadline and Budget Constraints

机译:具有截止日期和预算约束的QoS感知多目标优化Web服务选择算法

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摘要

The problem of QoS-aware multiobjective optimization is an important issue for Web services selection in distributed computing environment. In this paper, a novel algorithm called MOASS (multiobjective optimization algorithm for web service selection) is proposed through analyzing the genetic operators such as constraint handling, the initial population generation, fitness assignment, and diversity preservation. Compared with MOEAWP (Yu et al., 2007), simulation results show that the feasible objective region can be filled uniformly with the optimal solutions obtained by MOASS under different test applications. In the case of higher constraints especially, MOASS can obtain more high-quality and evenly distributed nondominated solutions than MOEAWP.
机译:QoS感知多目标优化问题是分布式计算环境中Web服务选择的重要问题。通过分析约束处理,初始种群生成,适应度分配和多样性保存等遗传算子,提出了一种新颖的算法,称为MOASS(Web服务选择的多目标优化算法)。与MOEAWP相比(Yu等,2007),仿真结果表明,在不同的测试应用下,用MOASS获得的最优解可以均匀地填充可行的目标区域。特别是在更高的约束条件下,与MOEAWP相比,MOASS可以获得更多高质量和均匀分布的非支配解决方案。

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