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2004
Springer

Phase Transition Properties of Clustered Travelling Salesman Problem Instances Generated with Evolutionary Computation

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Phase Transition Properties of Clustered Travelling Salesman Problem Instances Generated with Evolutionary Computation
Abstract. This paper introduces a generator that creates problem instances for the Euclidean symmetric travelling salesman problem. To fit real world problems, we look at maps consisting of clustered nodes. Uniform random sampling methods do not result in maps where the nodes are spread out to form identifiable clusters. To improve upon this, we propose an evolutionary algorithm that uses the layout of nodes on a map as its genotype. By optimising the spread until a set of constraints is satisfied, we are able to produce better clustered maps, in a more robust way. When varying the number of clusters in these maps and, when solving the Euclidean symmetric travelling salesman person using Chained Lin-Kernighan, we observe a phase transition in the form of an easy-hard-easy pattern.
Jano I. van Hemert, Neil Urquhart
Added 02 Jul 2010
Updated 02 Jul 2010
Type Conference
Year 2004
Where PPSN
Authors Jano I. van Hemert, Neil Urquhart
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