Self-Organizing Map for the Prize-Collecting Traveling Salesman Problem

  • Jan Faigl
  • Geoffrey A. Hollinger
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 295)

Abstract

In this paper, we propose novel adaptation rules for the self-organizing map to solve the prize-collecting traveling salesman problem (PC-TSP). The goal of the PC-TSP is to find a cost-efficient tour to collect prizes by visiting a subset of a given set of locations. In contrast with the classical traveling salesman problem, where all given locations must be visited, locations in the PC-TSP may be skipped at the cost of some additional penalty. Using the self-organizing map, locations for the final solution may be selected during network adaptation, and locations where visitation would be more expensive than their penalty can be avoided. We have applied the proposed self-organizing map learning procedure to autonomous data collection problems, where the proposed approach provides results competitive with an existing combinatorial solver.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Jan Faigl
    • 1
  • Geoffrey A. Hollinger
    • 2
  1. 1.Department of Computer Science and EngineeringCzech Technical University in PraguePragueCzech Republic
  2. 2.School of Mechanical, Industrial, and Manufacturing EngineeringOregon State UniversityCorvallisUSA

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