Evolutionary Computational Approaches to Solving the Multiple Traveling Salesman Problem Using a Neighborhood Attractor Schema

Authors:
Donald Sofge;Alan Schultz;Kenneth DeJong
Affiliations:
-;-;-
Venue:
Proceedings of the Applications of Evolutionary Computing on EvoWorkshops 2002: EvoCOP, EvoIASP, EvoSTIM/EvoPLAN
Year:
2002

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Abstract

This paper presents a variation of the Euclidean Traveling Salesman Problem (TSP), the Multiple Traveling Salesman Problem (MTSP), and compares a variety of evolutionary computation algorithms and paradigms for solving it. Techniques implemented, analyzed, and discussed herein with regard to MTSP include use of a neighborhood attractor schema (a variation on k-means clustering), the "shrink-wrap" algorithm for local neighborhood optimization, particle swarm optimization, Monte-Carlo optimization, and a range of genetic algorithms and evolutionary strategies.