Please use this identifier to cite or link to this item: http://repositorio.inesctec.pt/handle/123456789/5267
Title: A multi-population hybrid biased random key genetic algorithm for hop-constrained trees in nonlinear cost flow networks
Authors: Dalila Fontes
José Fernando Gonçalves
Issue Date: 2013
Abstract: Genetic algorithms and other evolutionary algorithms have been successfully applied to solve constrained minimum spanning tree problems in a variety of communication network design problems. In this paper, we enlarge the application of these types of algorithms by presenting a multi-population hybrid genetic algorithm to another communication design problem. This new problem is modeled through a hop-constrained minimum spanning tree also exhibiting the characteristic of flows. All nodes, except for the root node, have a nonnegative flow requirement. In addition to the fixed charge costs, nonlinear flow dependent costs are also considered. This problem is an extension of the well know NP-hard hop-constrained Minimum Spanning Tree problem and we have termed it hop-constrained minimum cost flow spanning tree problem. The efficiency and effectiveness of the proposed method can be seen from the computational results reported.
URI: http://repositorio.inesctec.pt/handle/123456789/5267
http://dx.doi.org/10.1007/s11590-012-0505-5
metadata.dc.type: article
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