Paper Info
Title
A Multi-Population Genetic Algorithm For Tree-Shaped Network Design Problems
Abstract
In this work we propose a multi-population genetic algorithm for tree-shaped network design problems using random keys. Recent literature on finding optimal spanning trees suggests the use of genetic algorithms. Furthermore, random keys encoding has been proved efficient at dealing with problems where the relative order of tasks is important. Here we propose to use random keys for encoding trees. The topology of these trees is restricted, since no path from the root vertex to any other vertex may have more than a pre-defined number of arcs. In addition, the problems under consideration also exhibit the characteristic of flows. Therefore, we want to find a minimum cost tree satisfying all demand vertices and the pre-defined number of arcs. The contributions of this paper are twofold: on one hand we address a new problem, which is an extension of the well known NP-hard hop-constrained MST problem since we also consider determining arc flows such that vertices requirements are met at minimum cost and the cost functions considered include a fixed cost component and a nonlinear flow routing component; on the other hand, we propose a new genetic algorithm to efficiently find solutions to this problem.
Year
Venue
Keywords
2009
IJCCI 2009: PROCEEDINGS OF THE INTERNATIONAL JOINT CONFERENCE ON COMPUTATIONAL INTELLIGENCE
Multi-population genetic algorithms, Random keys, Network design
Field
DocType
Citations 
Population,Mathematical optimization,Vertex (geometry),Network planning and design,Computer science,Fixed cost,Flow routing,Spanning tree,Genetic algorithm,Encoding (memory)
Conference
0
PageRank 
References 
Authors
0.34
12
2
Name
Order
Citations
PageRank
Dalila B. M. M. Fontes110211.77
José Fernando Gonçalves273637.31