Please use this identifier to cite or link to this item:
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.
metadata.dc.type: article
Appears in Collections:LIAAD - Other Publications

Files in This Item:
File Description SizeFormat 
P-006-8T0.pdf843.82 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.