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首页> 外文期刊>Journal of computer sciences >Strength Pareto Evolutionary Algorithm based Multi-Objective Optimization for Shortest Path Routing Problem in Computer Networks | Science Publications
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Strength Pareto Evolutionary Algorithm based Multi-Objective Optimization for Shortest Path Routing Problem in Computer Networks | Science Publications

机译:计算机网络最短路径路由问题的基于强度帕累托进化算法的多目标优化科学出版物

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摘要

> Problem statement: A new multi-objective approach, Strength Pareto Evolutionary Algorithm (SPEA), is presented in this paper to solve the shortest path routing problem. The routing problem is formulated as a multi-objective mathematical programming problem which attempts to minimize both cost and delay objectives simultaneously. Approach: SPEA handles the shortest path routing problem as a true multi-objective optimization problem with competing and noncommensurable objectives. Results: SPEA combines several features of previous multi-objective evolutionary algorithms in a unique manner. SPEA stores nondominated solutions externally in another continuously-updated population and uses a hierarchical clustering algorithm to provide the decision maker with a manageable pareto-optimal set. SPEA is applied to a 20 node network as well as to large size networks ranging from 50-200 nodes. Conclusion: The results demonstrate the capabilities of the proposed approach to generate true and well distributed pareto-optimal nondominated solutions.
机译: > 问题陈述:本文提出了一种新的多目标方法,即强度帕累托进化算法(SPEA),以解决最短路径路由问题。路由问题被表述为一个多目标数学规划问题,该问题试图同时最小化成本和延迟目标。 方法: SPEA将最短路径路由问题作为具有竞争和不可估量目标的真正多目标优化问题来处理。 结果: SPEA以独特的方式结合了以前的多目标进化算法的若干功能。 SPEA在外部将非控制解决方案存储在另一个不断更新的总体中,并使用分层聚类算法为决策者提供可管理的pareto-optimize集合。 SPEA可应用于20个节点的网络以及50-200个节点的大型网络。 结论:结果证明了该方法能够生成真实且分布良好的对等最优非支配解。

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