Design of an optimal communication network using multiobjective genetic optimization

R. Kumar, V.P. Krishnan, K.S. Santhanakrishnan
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引用次数: 1

Abstract

Designing an optimal network requires careful optimization of conflicting requirements. It is an NP hard problem. Traditional approaches to this problem have been based either on heuristics or on rigorous mathematical programming, queuing theory and network flow concepts. In this work, the authors describe the use of the multi-objective genetic optimization technique to obtain a Pareto front-a set of solutions which are optimal with respect to a set of constraints and noninferior to each other-for the network design problem. A prototype is developed and the simulator is currently being tested on different sets of inputs.
基于多目标遗传优化的最优通信网络设计
设计一个最优网络需要仔细优化相互冲突的需求。这是一个NP困难问题。解决这一问题的传统方法要么基于启发式方法,要么基于严格的数学规划、排队论和网络流概念。在这项工作中,作者描述了使用多目标遗传优化技术来获得网络设计问题的帕累托前沿-一组相对于一组约束且彼此不劣的最优解。一个原型正在开发,模拟器目前正在不同的输入集上进行测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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