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RELIABLE COMMUNICATION NETOWRK DESIGN WITH EVOLUTIONARY ALGORITHMS

机译:进化算法的可靠通信网络设计

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摘要

For the reliable communication network design (RCND) problem unreliable links are available, each bearing several options which have different levels of reliability and varying costs. The goal is to find the most cost-effective communication network design that satisfies a predefined overall reliability constraint. This paper presents two new evolutionary algorithm (EA) approaches to solving the RCND problem: LaBORNet and BaBORNet. LaBORNet uses an encoding that represents the network topology as well as the used link options while repairing infeasible solutions using an additional repair heuristic (CURE). BaBORNet encodes only the network topology and determines the link options by using the repair heuristic CURE as a local search method. The experimental results show that the new EA approaches using repair heuristics outperform existing EA approaches from the literature using penalties for infeasible solutions. They also find better solutions for existing problems from the literature, as well as for new and larger test problems.
机译:对于可靠的通信网络设计(RCND)问题,存在不可靠的链接,每个链接都有几种选择,这些选择具有不同的可靠性和不同的成本。目标是找到满足预定义的总体可靠性约束的最具成本效益的通信网络设计。本文提出了两种用于解决RCND问题的新进化算法(EA)方法:LaBORNet和BaBORNet。 LaBORNet使用一种表示网络拓扑以及所用链接选项的编码,同时使用其他修复启发式(CURE)修复不可行的解决方案。 BaBORNet仅对网络拓扑进行编码,并通过使用修复启发式CURE作为本地搜索方法来确定链接选项。实验结果表明,使用修复启发式方法的新EA方法优于文献中使用不可行解决方案的罚款的现有EA方法。他们还从文献中为现有问题以及新的和较大的测试问题找到了更好的解决方案。

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