• Title/Summary/Keyword: Chinese Postman Problem(CPP)

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A Genetic Algorithm for the Chinese Postman Problem on the Mixed Networks (유전자 알고리즘을 이용한 혼합 네트워크에서의 Chinese Postman Problem 해법)

  • Jun Byung Hyun;Kang Myung Ju;Han Chi Geun
    • Journal of the Korea Society of Computer and Information
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    • v.10 no.1 s.33
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    • pp.181-188
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    • 2005
  • Chinese Postman Problem (CPP) is a problem that finds a shortest tour traversing all edges or arcs at least once in a given network. The Chinese Postman Problem on Mixed networks (MCPP) is a Practical generalization of the classical CPP and it has many real-world applications. The MCPP has been shown to be NP-complete. In this paper, we transform a mixed network into a symmetric network using virtual arcs that are shortest paths by Floyd's algorithm. With the transformed network, we propose a Genetic Algorithm (GA) that converges to a near optimal solution quickly by a multi-directional search technique. We study the chromosome structure used in the GA and it consists of a path string and an encoding string. An encoding method, a decoding method, and some genetic operators that are needed when the MCPP is solved using the Proposed GA are studied. . In addition, two scaling methods are used in proposed GA. We compare the performance of the GA with an existing Modified MDXED2 algorithm (Pearn et al. , 1995) In the simulation results, the proposed method is better than the existing methods in case the network has many edges, the Power Law scaling method is better than the Logarithmic scaling method.

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GENIIS, a New Hybrid Algorithm for Solving the Mixed Chinese Postman Problem

  • Choi, Myeong-Gil;Thangi, Nguyen-Manh;Hwang, Won-Joo
    • The Journal of Information Systems
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    • v.17 no.3
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    • pp.39-58
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    • 2008
  • Mixed Chinese Postman Problem (MCPP) is a practical generalization of the classical Chinese Postman Problem (CPP) and it could be applied in many real world. Although MCPP is useful in terms of reality, MCPP has been proved to be a NP-complete problem. To find optimal solutions efficiently in MCPP, we can reduce searching space to be small effective searching space containing optimal solutions. We propose GENIIS methodology, which is a kind of hybrid algorithm combines the approximate algorithms and genetic algorithm. To get good solutions in the effective searching space, GENIIS uses approximate algorithm and genetic algorithm. This paper validates the usefulness of the proposed approach in a simulation. The results of our paper could be utilized to increase the efficiencies of network and transportation in business.

Adaptive Application of CPP Algorithm to Test Suite Generation for Protocol Conformance Testing (프로토콜 적합성 시험항목 생성시 CPP 알고리즘의 적응적 적용 방안)

  • Kim, Chul
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.12 no.6
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    • pp.597-604
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    • 2019
  • In this paper, we propose an improved method on an adaptive application of the CPP(Chinese Postman Problem) algorithm to the protocol test suite generation for conformance testing. Also, we present an example application of this CPP algorithm to B-ISDN Q.2931 call/connection control procedure for the purpose of showing how it can be adapted to generate a test suite for conformance testing of a communication protocol. The proposed method has an advantage of an optimization technique which finds a minimum cost of test suite from a standardized specification, so this optimization technique of the CPP algorithm can be practically applied to a real environment for testing a conformity of a protocol implementation.

Design and Implementation of Genegtic Algorithm Simulation System for A Path Finding (유전자 알고리즘을 이용한 경로찾기 시뮬레이션 시스템 설계 및 구현)

  • Kang, Myung-Ju;Park, Kwang-Yong
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2010.07a
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    • pp.103-107
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    • 2010
  • 게임이나 네비게이션 시스템, 관광경로 설계에 있어서 경로찾기는 매우 중요한 부분 중의 하나이다. 일반적으로 TSP(Traveling Salesman Problem), RPP(Rural Postman Problem), CPP(Chinese Postman Problem)와 같은 경로찾기 문제들은 일반적인 알고리즘으로 최적해를 구할 수 없다. 문제크기가 커질수록 해집합이 폭발적으로 커짐으로써 전체 해집합을 탐색하는데 많은 비용이 든다. 따라서, 이러한 문제들은 유전알고리즘이나 Simulated Annealing과 같은 휴리스틱 알고리즘을 이용하여 근사최적 경로를 찾는다. 본 논문에서는 이와 같은 경로찾기 문제의 근사 최적해를 구하기 위한 시뮬레이션 시스템을 설계하고 구현하였다. 본 연구에서 구현한 시뮬레이션 시스템에는 유전알고리즘 엔진(GA 엔진)과 사용자 인터페이스를 제공한다. 사용자 인터페이스는 유전알고리즘에 사용될 파라미터를 설정하는 부분이며, GA 엔진은 유전알고리즘의 연산자들을 제공하는 부분이다. 본 논문에서 구현한 시뮬레이션 시스템은 게임과 같은 경로찾기 등에 활용될 수 있다.

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