Article ID: | iaor20072609 |
Country: | United Kingdom |
Volume: | 2 |
Issue: | 1 |
Start Page Number: | 47 |
End Page Number: | 63 |
Publication Date: | Jan 2007 |
Journal: | International Journal of Operational Research |
Authors: | Ferrell William G., Kurz Mary Beth, Samanlioglu Funda, Tangudu Sarat |
Keywords: | heuristics: genetic algorithms |
This paper describes a methodology that finds approximate and sometimes optimal solutions to the symmetric Travelling Salesman Problem (TSP) using a hybrid approach that combines a Random-Key Genetic Algorithm (RKGA) with a local search procedure. The random keys representation ensures that feasible tours are constructed during the application of genetic operators, whereas the genetic algorithm approach with local search efficiently generates optimal or near-optimal solutions. The results of experiments are provided that use examples taken from a well-known online library to confirm the quality of the proposed algorithm.