Genetically improved presequences for euclidean traveling salesman problems

Authors:
D. M. Tate;C. Tunasar;A. E. Smith
Affiliations:
Department of Industrial Engineering 1048 Benedum Hall, University of Pittsburgh Pittsburgh, PA 15261, U.S.A.;Department of Industrial Engineering 1048 Benedum Hall, University of Pittsburgh Pittsburgh, PA 15261, U.S.A.;Department of Industrial Engineering 1048 Benedum Hall, University of Pittsburgh Pittsburgh, PA 15261, U.S.A.
Venue:
Mathematical and Computer Modelling: An International Journal
Year:
1994

Citing 8
Cited 0

Heuristics based on spacefilling curves for combinatorial problems in Euclidean space

Management Science
Genetic algorithms and job shop scheduling

Proceedings of the 12th annual conference on Computers and industrial engineering
New search spaces for sequencing problems with application to job shop scheduling

Management Science
Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
Distributed genetic algorithms for the floorplan design problem

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
An O(N log N) planar travelling salesman heuristic based on spacefilling curves

Operations Research Letters
Optimization of a 532-city symmetric traveling salesman problem by branch and cut

Operations Research Letters
Worst-case examples for the spacefilling curve heuristic for the Euclidean traveling salesman problem

Operations Research Letters

Quantified Score

Hi-index	0.98

Visualization

Abstract

The spacefilling curve (SFC) method of Bartholdy and Platzman is an extremely fast heuristic for the Euclidean Traveling Salesman Problem. The authors show how genetic search over a parametrized family of spacefilling curves can be used to improve the quality of the the tours generated by SFC. The computational effort required grows slowly as a function of problem size, and the tours obtained define robust presequences for repetitive problems in which only a subset of all cities will be present in any given problem instance.