산업경영시스템학회지 (Journal of Korean Society of Industrial and Systems Engineering)

  • 제42권3호
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  • Pages.1-7
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  • 2019
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  • 2005-0461(pISSN)
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  • 2287-7975(eISSN)
한국산업경영시스템학회 (Society of Korea Industrial and System Engineering)
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순회 판매원 문제 해결을 위한 개미집단 최적화 알고리즘 개선

Improvement of Ant Colony Optimization Algorithm to Solve Traveling Salesman Problem

  • 장주영 (금오공과대학교 산업공학부) ;
  • 김민제 (금오공과대학교 산업공학부) ;
  • 이종환 (금오공과대학교 산업공학부)
  • Jang, Juyoung (Department of Industrial Engineering, Kumoh National Institute of Technology) ;
  • Kim, Minje (Department of Industrial Engineering, Kumoh National Institute of Technology) ;
  • Lee, Jonghwan (Department of Industrial Engineering, Kumoh National Institute of Technology)
  • 투고 : 2019.03.06
  • 심사 : 2019.04.27
  • 발행 : 2019.09.30
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초록

It is one of the known methods to obtain the optimal solution using the Ant Colony Optimization Algorithm for the Traveling Salesman Problem (TSP), which is a combination optimization problem. In this paper, we solve the TSP problem by proposing an improved new ant colony optimization algorithm that combines genetic algorithm mutations in existing ant colony optimization algorithms to solve TSP problems in many cities. The new ant colony optimization algorithm provides the opportunity to move easily fall on the issue of developing local optimum values of the existing ant colony optimization algorithm to global optimum value through a new path through mutation. The new path will update the pheromone through an ant colony optimization algorithm. The renewed new pheromone serves to derive the global optimal value from what could have fallen to the local optimal value. Experimental results show that the existing algorithms and the new algorithms are superior to those of existing algorithms in the search for optimum values of newly improved algorithms.

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참고문헌

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