TY  - CONF
T1  - Phase transition properties of clustered travelling salesman problem instances generated with evolutionary computation
T2  - LNCS
Y1  - 2004
A1  - van Hemert, J. I.
A1  - Urquhart, N. B.
ED  - Xin Yao
ED  - Edmund Burke
ED  - Jose A. Lozano
ED  - Jim Smith
ED  - Juan J. Merelo-Guerv\'os
ED  - John A. Bullinaria
ED  - Jonathan Rowe
ED  - Peter Ti\v{n}o Ata Kab\'an
ED  - Hans-Paul Schwefel
KW  - evolutionary computation
KW  - problem evolving
KW  - travelling salesman
AB  - 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.
JF  - LNCS
PB  - Springer-Verlag
CY  - Birmingham, UK
VL  - 3242
SN  - 3-540-23092-0
UR  - http://www.vanhemert.co.uk/files/clustered-phase-transition-tsp.tar.gz
ER  -