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Optimal Solution of a Large-scale Travelling Salesman Problem applying DNN and k-opt

DNN과 k-opt를 적용한 대규모 외판원 문제의 최적 해법

  • Lee, Sang-Un (Dept. of Multimedia Eng., Gangneung-Wonju National University)
  • 이상운 (강릉원주대학교 과학기술대학 멀티미디어공학과)
  • Received : 2015.02.08
  • Accepted : 2015.08.07
  • Published : 2015.08.31

Abstract

This paper introduces a heuristic algorithm to NP-hard travelling salesman problem. The proposed algorithm, in its bid to determine initial path, applies SW-DNN, DW-DNN, and DC-DNN, which are modified forms of the prevalent Double-sided Nearest Neighbor Search and searches the minimum value. As a part of its optimization process on the initial solution, it employs 2, 2.5, 3-opt of a local search k-opt on candidate delete edges and 4-opt on undeleted ones among them. When tested on TSP-1 of 26 European cities and TSP-2 of 49 U.S. cities, the proposed algorithm has successfully obtained optimal results in both, disproving the prevalent disbelief in the attainability of the optimal solution and making itself available as a general algorithm for the travelling salesman problem.

본 논문은 지금까지 해결하지 못한 난제 중 하나인 외판원 문제의 최적 해를 구하는 발견적 알고리즘을 제안한다. 제안된 알고리즘은 초기 경로를 결정하기 위해 기존의 DNN을 변형한 SW-DNN, DW-DNN과 DC-DNN을 제안하였다. 초기 해는 DNN, SW-DNN, DW-DNN과 DC-DNN을 적용하여 최소 경로 길이를 가진 방법을 선택한다. 초기 해에 대해 최적 해를 구하기 위해 먼저 삭제 대상 간선을 선택하는 방법을 결정하였으며, 이들 간선들에 대해 지역 탐색 방법인 k-opt 중에서 2, 2.5, 3-opt를 먼저 적용하고, 삭제 대상 간선들 중 삭제되지 않은 간선들에 대해 4-opt를 적용하였다. 제안된 알고리즘을 대규모의 TSP인 26개의 유럽 도시들을 방문하는 TSP-1과 49개의 미국 도시들을 방문하는 TSP-2에 적용한 결과 모두 최적 해를 구하는데 성공하였다. 제안된 알고리즘은 지금까지 발견적 방법으로는 TSP의 최적 해를 구하지 못한다는 미신을 타파하였고, TSP의 알고리즘으로 적용할 수 있을 것이다.

Keywords

References

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