Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
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An Integer Programming-based Local Search for the Set Covering Problem

집합 커버링 문제를 위한 정수계획법 기반 지역 탐색

  • Hwang, Jun-Ha (Dept. of Computer Engineering, Kumoh National Institute of Technology)
  • 황준하 (금오공과대학교 컴퓨터공학과)
  • Received : 2014.07.22
  • Accepted : 2014.09.11
  • Published : 2014.10.31
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Abstract

The set covering problem (SCP) is one of representative combinatorial optimization problems, which is defined as the problem of covering the m-rows by a subset of the n-columns at minimal cost. This paper proposes a method utilizing Integer Programming-based Local Search (IPbLS) to solve the set covering problem. IPbLS is a kind of local search technique in which the current solution is improved by searching neighborhood solutions. Integer programming is used to generate neighborhood solution in IPbLS. The effectiveness of the proposed algorithm has been tested on OR-Library test instances. The experimental results showed that IPbLS could search for the best known solutions in all the test instances. Especially, I confirmed that IPbLS could search for better solutions than the best known solutions in four test instances.

집합 커버링 문제는 대표적인 조합 최적화 문제들 중 하나로서 n개의 열로부터 일부를 선택하여 m개의 행을 커버하되 비용을 최소화하는 문제로 정의된다. 본 논문에서는 집합 커버링 문제를 해결하기 위한 정수 계획법 기반 지역 탐색의 적용 방안을 제시하고 있다. 정수계획법 기반 지역 탐색은 이웃해를 탐색하여 현재해를 반복적으로 개선하는 지역 탐색 기법의 일종으로서 이웃해를 생성하기 위한 알고리즘으로 정수계획법을 사용한다. 본 논문에서 제시한 기법의 효과를 검증하기 위해 OR-Library의 테스트 데이터를 대상으로 실험을 수행하였다. 실험 결과, 모든 테스트 데이터에 있어서 정수계획법 기반 지역 탐색을 통해 지금까지 알려진 가장 좋은 해를 탐색할 수 있었다. 특히 4개의 테스트 데이터에 대해서는 지금까지 알려진 가장 좋은 해보다 더 좋은 해를 도출할 수 있음을 확인할 수 있었다.

Keywords

Acknowledgement

Supported by : 금오공과대학교

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