Genetic Algorithms With Immigrants and Memory Schemes for Dynamic Shortest Path Routing Problems in Mobile Ad Hoc Networks
Genetic Algorithms With Immigrants and Memory Schemes for Dynamic Shortest Path Routing Problems in Mobile Ad Hoc Networks
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DOI：
10.1109/tsmcc.2009.2023676
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
Shengxiang Yang;Hui Cheng;Fang Wang
中科院分区：
文献类型：
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作者：
Shengxiang Yang;Hui Cheng;Fang Wang
近年来，静态最短路径（SP）问题已经使用智能优化技术得到了很好的解决，例如，人工神经网络、遗传算法（GA）、粒子群优化等。然而，随着无线通信的发展，出现了越来越多的移动的无线网络，例如，移动的网络[移动的自组织网络（MANN）]、无线传感器网络等。移动的无线网络中最重要的特征之一是拓扑动态性，即，网络拓扑由于能量守恒或节点移动性而随时间改变。因此，移动自组网中的SP路由问题是一个动态优化问题。在本文中，我们提出了使用遗传算法与移民和记忆计划，以解决动态SP路由问题的移动自组网。我们认为移动自组网是目标系统，因为它们代表了新一代无线网络。实验结果表明，这些移民和基于记忆的遗传算法可以快速适应环境变化（即，网络拓扑改变），并在每次改变之后产生高质量的解决方案。
In recent years, the static shortest path (SP) problem has been well addressed using intelligent optimization techniques, e.g., artificial neural networks, genetic algorithms (GAs), particle swarm optimization, etc. However, with the advancement in wireless communications, more and more mobile wireless networks appear, e.g., mobile networks [mobile ad hoc networks (MANETs)], wireless sensor networks, etc. One of the most important characteristics in mobile wireless networks is the topology dynamics, i.e., the network topology changes over time due to energy conservation or node mobility. Therefore, the SP routing problem in MANETs turns out to be a dynamic optimization problem. In this paper, we propose to use GAs with immigrants and memory schemes to solve the dynamic SP routing problem in MANETs. We consider MANETs as target systems because they represent new-generation wireless networks. The experimental results show that these immigrants and memory-based GAs can quickly adapt to environmental changes (i.e., the network topology changes) and produce high-quality solutions after each change.