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

Korean Society of Computer Information (한국컴퓨터정보학회)
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Genetic Algorithm based Pathfinding System for Analyzing Networks

네트워크 분석을 위한 유전 알고리즘 기반 경로탐색 시스템

  • Kim, Jun-Woo (Dept. of Industrial and Management Systems Engineering, Dong-A University)
  • 김준우 (동아대학교 산업경영공학과)
  • Received : 2013.10.21
  • Accepted : 2013.12.06
  • Published : 2014.01.29
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Abstract

This paper proposes GAPS, a practical genetic algorithm based pathfinding system for conveniently analyzing various networks. To this end, the GAPS is developed through integration of the intuitive graphic user interface for network modeling, the database management system for managing the data generated in modeling and exploring procedures, and a simple genetic algorithm for analyzing a wide range of networks. Especially, previous genetic algorithms are not appropriate for analyzing the networks with many dead-ends where there are few feasible paths between the given two nodes, however, GAPS is based on the genetic algorithm with the fitness function appropriate for evaluating both feasible and infeasible paths, which enables GAPS to analyze a wide range of networks while maintaining the diversity of the population. The experiment results reveal that GAPS can be used to analyze both networks with many dead-ends and networks with few dead-ends conveniently, and GAPS has several advantages over the previous genetic algorithms for pathfinding problems.

본 논문은 다양한 네트워크를 편리하게 분석할 수 있는 실용적인 유전 알고리즘 기반 경로탐색 시스템인 GAPS를 제안하고자 한다. 이러한 목적을 위해 GAPS는 네트워크 모델링을 위한 직관적인 그래픽 사용자 인터페이스와 모델링 및 탐색 과정에서 발생하는 데이터들을 관리하기 위한 데이터베이스 관리 시스템, 다양한 네트워크를 분석하기 위해 개발된 간단한 유전 알고리즘을 결합하여 개발되었다. 특히, 기존의 유전 알고리즘들이 단락이 많고 두 개 노드 간 실행가능 경로 수가 많지 않은 네트워크를 분석하는데 적합하지 않았던 반면, GAPS는 실행가능 경로와 실행불가능 경로를 모두 적절히 평가할 수 있는 적합도 함수를 사용하는 유전 알고리즘에 기반하고 있어 해 집단의 다양성을 유지하면서 다양한 네트워크들을 분석할 수 있다. 실험결과, GAPS를 통해 단락이 많은 네트워크와 단락이 적은 네트워크를 모두 편리하게 분석할 수 있다는 점과, GAPS가 기존의 경로탐색문제를 위한 유전 알고리즘들과 대비되는 장점을 갖고 있음을 확인할 수 있었다.

Keywords

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