Optimization of the Nested Monte-Carlo Algorithm on the Traveling Salesman Problem with Time Windows

Rimmel A., Teytaud F., Cazenave T.

Conference on EvoApplications 2011: EvoCOMPLEX, EvoGAMES, EvoIASP, EvoINTELLIGENCE, EvoNUM, AND EvoSTOC, Torino, Italy, 27 - 29 April 2011, vol.6625, pp.501-502 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 6625
  • City: Torino
  • Country: Italy
  • Page Numbers: pp.501-502
  • Istanbul Technical University Affiliated: No

Abstract

The traveling salesman problem with time windows is known to be a really difficult benchmark for optimization algorithms. In this paper, we are interested in the minimization of the travel cost. To solve this problem, we propose to use the nested Monte-Carlo algorithm combined with a Self-Adaptation Evolution Strategy. We compare the efficiency of several fitness functions. We show that with our technique we can reach the state of the art solutions for a lot of problems in a short period of time.