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An improved greedy genetic algorithm for solving travelling salesman problem

  • Zhenchao Wang*
  • , Haibin Duan
  • , Xiangyin Zhang
  • *Corresponding author for this work
  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Genetic algorithm (GA) is too dependent on the initial population and a lack of local search ability. In this paper, an improved greedy genetic algorithm (IGAA) is proposed to overcome the above-mentioned limitations. This novel type of greedy genetic algorithm is based on the base point, which can generate good initial population, and combine with hybrid algorithms to get the optimal solution. The proposed algorithm is tested with the Traveling Salesman Problem (TSP), and the experimental results demonstrate that the proposed algorithm is a feasible and effective algorithm in solving complex optimization problems.

Original languageEnglish
Title of host publication5th International Conference on Natural Computation, ICNC 2009
PublisherIEEE Computer Society
Pages374-378
Number of pages5
ISBN (Print)9780769537368
DOIs
StatePublished - 2009
Event5th International Conference on Natural Computation, ICNC 2009 - Tianjian, China
Duration: 14 Aug 200916 Aug 2009

Publication series

Name5th International Conference on Natural Computation, ICNC 2009
Volume5

Conference

Conference5th International Conference on Natural Computation, ICNC 2009
Country/TerritoryChina
CityTianjian
Period14/08/0916/08/09

Keywords

  • Base point
  • Genetic algorithm(GA)
  • Greedy algorithm
  • Improved greedy genetic algorithm(IGAA)
  • Traveling salesman problem

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