A Study of the Effects of Clustering and Local Search on Radio Network Design: Evolutionary Computation Approaches
作者： Yago Saez , Fernando Zazo , Pedro Isasi
DOI: 10.1109/HIS.2008.99
关键词: Evolutionary computation 、 Cluster analysis 、 Genetic representation 、 Computer science 、 Human-based evolutionary computation 、 Theoretical computer science 、 Artificial intelligence 、 Evolutionary programming 、 Machine learning 、 Interactive evolutionary computation 、 Memetic algorithm 、 Cultural algorithm
摘要: The goal of this paper is twofold. First, we want to make a study about how evolutionary computation techniques can efficiently solve the radio network design problem. For test several within OPLINK experimental framework and compare them. Second, propose clustering approach 2-OPT in order improve results obtained by algorithms. Experiments carried out provide empirical evidence clustering-based help improving all algorithms tested. Extensive computational tests, including ones without 2-OPT, are performed with three algorithms: genetic algorithms, memetic chromosome appearance probability matrix
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