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Performance Evaluation Of Vertical Handoff Decision Algorithms In Heterogeneous Wireless Networks, Min Liu, Zhong-Cheng Li, Xiao-Bing Guo, Eryk Dutkiewicz, De-Kui Zhang
Performance Evaluation Of Vertical Handoff Decision Algorithms In Heterogeneous Wireless Networks, Min Liu, Zhong-Cheng Li, Xiao-Bing Guo, Eryk Dutkiewicz, De-Kui Zhang
Faculty of Informatics - Papers (Archive)
In recent years, many research works have focused on vertical handoff (VHO) decision algorithms. However, evaluation scenarios in different papers are often quite different and there is no consensus on how to evaluate performance of VHO algorithms. In this paper, we address this important issue by proposing an approach for systematic and thorough performance evaluation of VHO algorithms. Firstly we define the evaluation criteria for VHO with two metrics: matching ratio and average ping-pong number. Subsequently we analyze the general movement characteristics of mobile hosts and identify a set of novel performance evaluation models for VHO algorithms. Equipped with these …
Fitness Evaluation For Structural Optimisation Genetic Algorithms Using Neural Networks, Koren Ward, Timothy J. Mccarthy
Fitness Evaluation For Structural Optimisation Genetic Algorithms Using Neural Networks, Koren Ward, Timothy J. Mccarthy
Faculty of Informatics - Papers (Archive)
This paper relates to the optimisation of structural design using Genetic Algorithms (GAs) and presents an improved method for determining the fitness of genetic codes that represent possible design solutions by using a neural network to generalize fitness. Two problems that often impede design optimization using genetic algorithms are expensive fitness evaluation and high epistasis. In this paper we show that by using a neural network as a fitness approximator, optimal solutions to certain design problems can be achieved in significantly less generations and with considerably less fitness evaluations.