The EAX Algorithm Considering Diversity Loss

  • Yuichi Nagata
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3242)


The edge assembly crossover (EAX) is considered the best available crossover for traveling salesman problems (TSPs). In this paper, a modified EAX algorithm is proposed. The key idea is to maintain population diversity by eliminating any exchanges of edges by the crossover that does not contribute to an improved evaluation value. The proposed method is applied to several benchmark problems up to 4461 cities. Experimental results shows that the proposed method works better than other genetic algorithms using other improvements of the EAX. The proposed method can reach optimal solutions in most benchmark problems up to 2392 cities with probabilities higher than 90%. For the fnl4461 problem, this method can reach the optimal solution with a 60% probability for a population size of 300 – an extremely small population compared to that needed in previous studies.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Yuichi Nagata
    • 1
  1. 1.Graduate School of Information SciencesJapan Advanced Institute of Science and Technology 

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