Property analysis of symmetric travelling salesman problem instances acquired through evolution

Computer Science – Neural and Evolutionary Computing

Scientific paper

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To be published in G. Raidl and J. Gottlieb, editors, Evolutionary Computation in Combinatorial Optimization, Springer Lecture

Scientific paper

We show how an evolutionary algorithm can successfully be used to evolve a set of difficult to solve symmetric travelling salesman problem instances for two variants of the Lin-Kernighan algorithm. Then we analyse the instances in those sets to guide us towards deferring general knowledge about the efficiency of the two variants in relation to structural properties of the symmetric travelling sale sman problem.

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