Statistical properties analysis of real world tournament selection in genetic algorithms

2011 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments (CIDUE)

Yang²

2011

Abstract-Clustering can help aggregate the topology information and reduce the size of routing tables in a mobile ad hoc network (MANET). To achieve fairness and even energy consumption, each clusterhead should ideally support the same number of cluster members. Moreover, one of the most important characteristics in MANETs is the topology dynamics, that is, the network topology changes over time due to energy conservation or node mobility. Therefore, for a dynamic and complex system like MANET, an effective clustering algorithm should efficiently adapt to each topology change and produce the new load balanced solution quickly. The maintenance of the cluster structure should be as stable as possible to reduce overhead. It requires that the new solution should try to keep most of the good parts in the previous solution. In this paper, we propose to use elitism-based immigrants genetic algorithm (EIGA) to solve the dynamic load balanced clustering problem in MANETs. Each individual represents a feasible clustering structure and its fitness is evaluated based on the load balance metric. Immigrants are introduced to help the population to handle the topology dynamics and produce new and closely related solutions. The experimental results show that EIGA can quickly adapt to the environmental changes (i.e., the network topology change) and produce highquality solutions after each change.

Section: Selection Schemementioning

confidence: 99%

Genetic algorithms with elitism-based immigrants for dynamic load balanced clustering problem in mobile ad hoc networks

2011 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments (CIDUE)

Yang²

2011

“…The selection of chromosomes is based on the fitness value. We adopt the scheme of pair-wise tournament selection without replacement (Lee et al, 2008) as it is simple and effective.…”

Section: Selection Schemementioning

confidence: 99%

Genetic algorithms with immigrants schemes for dynamic multicast problems in mobile ad hoc networks

Engineering Applications of Artificial Intelligence

Yang

2010

a b s t r a c tIn this paper, the problem of dynamic quality-of-service (QoS) multicast routing in mobile ad hoc networks is investigated. Lots of interesting works have been done on multicast since it is proved to be a NP-hard problem. However, most of them consider the static network scenarios only and the multicast tree cannot adapt to the topological changes. With the advancement in communication technologies, more and more wireless mobile networks appear, e.g., mobile ad hoc networks (MANETs). In a MANET, the network topology keeps changing due to its inherent characteristics such as the node mobility and energy conservation. Therefore, an effective multicast algorithm should track the topological changes and adapt the best multicast tree to the changes accordingly. In this paper, we propose to use genetic algorithms with immigrants schemes to solve the dynamic QoS multicast problem in MANETs. MANETs are considered as target systems because they represent a new generation of wireless networks. In the construction of the dynamic network environments, two models are proposed and investigated. One is named as the general dynamics model in which the topologies are changed due to that the nodes are scheduled to sleep or wake up. The other is named as the worst dynamics model, in which the topologies are altered because some links on the current best multicast tree are removed. Extensive experiments are conducted based on both of the dynamic network models. The experimental results show that these immigrants based genetic algorithms can quickly adapt to the environmental changes (i.e., the network topology changes) and produce high quality solutions following each change.

“…For the routing problems, the path-oriented encoding and the path-based crossover and mutation are also very popular [3]. For the selection scheme, the pair-wise tournament selection without replacement [6] is employed and the tournament size is 2.…”

Section: Design Of Ga For Sp Problemmentioning

confidence: 99%

Multi-population Genetic Algorithms with Immigrants Scheme for Dynamic Shortest Path Routing Problems in Mobile Ad Hoc Networks

Applications of Evolutionary Computation

Yang

2010

Abstract. 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 ad hoc network (MANET), wireless mesh network, etc. One of the most important characteristics in mobile wireless networks is the topology dynamics, that is, the network topology changes over time due to energy conservation or node mobility. Therefore, the SP problem turns out to be a dynamic optimization problem in mobile wireless networks. In this paper, we propose to use multi-population GAs with immigrants scheme to solve the dynamic SP problem in MANETs which is the representative of new generation wireless networks. The experimental results show that the proposed GAs can quickly adapt to the environmental changes (i.e., the network topology change) and produce good solutions after each change.