• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.181-188
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• 2007

Undirected Rural Postman Problem(URPP) is a problem that finds a shortest tour traversing the given arcs at least once in a given network. The URPP is one of the basic network problems used in solving the various real-world problems. And it is known as NP-Complete. URPP is an arc-oriented problem that the direction of a tour in an arc has to be considered. Hence, In URPP, it is difficult to use the algorithm for Traveling Salesman Problem (TSP), which is a node-oriented problem, directly. This paper proposes the decoding algorithm using graph transformation in the genetic algorithm for URPP. That is, you can find the entire tour traversing without considering the direction of arcs by transforming the arc-oriented graph into the node-oriented graph. This paper compares the performances of the proposed algorithm with an existing algorithm. In the simulation results, the proposed algorithm obtained better than the existing algorithm

• Journal of the Korea Society of Computer and Information
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• v.21 no.9
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• pp.79-84
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• 2016

In this paper we consider the problem of finding the triplet (S,${\pi}$,f), where $S{\subseteq}V$, ${\pi}$ is a sequence of nodes in S and $f:V{\backslash}S{\rightarrow}S$ for a given complete graph G=(V,E). In particular, there exist two costs, $c^V_{uv}$ and $c^D_{uv}$ for $(u,v){\in}E$, and the cost of triplet (S,${\pi}$,f) is defined as $\sum_{i=1}^{{\mid}S{\mid}}c^V_{{\pi}(i){\pi}(i+1)}+2$ ${\sum_{u{\in}V{\backslash}S}c^D_{uf(u)}$. This problem is motivated by the integrated routing of the vehicle and drone for urban delivery services. Since a well-known NP-complete TSP (Traveling Salesman Problem) is a special case of our problem, we cannot expect to have any polynomial-time algorithm unless P=NP. Furthermore, for practical purposes, we may not rely on time-exhaustive enumeration method such as branch-and-bound and branch-and-cut. This paper suggests the simple heuristic which is motivated by the MST (minimum spanning tree)-based approximation algorithm and neighborhood search heuristic for TSP.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.39
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• pp.9-18
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• 1996

Many algorithms have been developed for optimizing the asymmectric traveling salesman problem known as a representative NP-Complete problem. The most efficient ones of them are branch and bound algorithms based on the subtour elimination approach. To increase efficiency of the branch and bound algorithm. number of decision nodes should be decreased. For this the minimum bound that is more close at the optimal solution should be found or an effective bounding strategy should be used. If the optimal solution has been known, we may apply it usefully to branching. Because a good feasible solution should be found as soon as possible and have similar features of the optimal solution. By the way, the upper bound solution in branch and bound algorithm is most close at the optimal solution. Therefore, the upper bound solution can be used instead of the optimal solution and information of which can be applied to new branching criteria. As mentioned above, this paper will propose an effective branching rule using the information of the upper bound solution in the branch and bound algorithm. And superiority of the new branching rule will be shown by comparing with Bellmore-Malone's one and carpaneto-Toth's one that were already proposed.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10b
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• pp.1373-1376
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• 2000

외판원 문제(Traveling Salesman Problem)는 주어진 n개의 도시들과 그 도시들간의 거리 비용이 주어졌을 매, 처음 출발도시에서부터 정확히 한 도시는 한 번씩만 방문하여 다시 출발도시로 돌아오면서 방문한 도시들을 연결하는 최소의 비용이 드는 경로를 찾는 문제로 최적해(optimal value)를 구하는 것은 전형적인 NP-완전 문제중의 하나이다[2,4,5, 8]. 따라서 이들의 수행시간을 줄이고자 하는 연구가 많이 진행된다. 본 논문에서는 외판원 문제의 최적의 해를 구하는데. 휴리스틱 알고리즘인 최근접 휴리스틱을 이용한다. 물론 수행 시간을 줄이고자 최적화 문제에서 좋은 성능을 보이는 유전 알고리즘 (Genetic Algorithm)으로 얻은 근사해(near optimal)를 초기 분기 함수로 사용하고, 근거리 통신망(Local Area Network)에 기반한 분산 처리 환경에서 여러 프로세서에 분산시켜 병렬성을 살린다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.439-442
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• 2003

In order to solve the difficulties of parameter settings in SA algorithm, an improved practical SA algorithm is proposed by employing the threading techniques, appropriate software structures, and dynamic adjustments of temperature parameters. Threads provide a mechanism to realize a parallel processing under a disperse environment by controlling the flux of internal information of an application. Thread services divide a process by multiple processes leading to parallel processing of information to access common data. Therefore, efficient search is achieved by multiple search processes, different initial conditions, and automatic temperature adjustments. The proposed are methods are evaluated, for three types of Traveling Salesman Problem (TSP) (random-tour, fractal-tour, and TSPLIB test data)are used for the performance evaluation. The experimental results show that the computational time is 5％ decreased comparing to conventional SA algorithm, furthermore there is no need for manual parameter settings. These results also demonstrate that the proposed method is applicable to real-world vehicle routing problems.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.315-322
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• 2006

Ant Colony System(ACS) is easily applicable to the traveling salesman problem(TSP) and it has demonstrated good performance on TSP. Recently, ACS has been emerged as the useful tool for the pattern recognition, feature extraction, and edge detection. The edge detection is wifely utilized in the area of document analysis, character recognition, and face recognition. However, the conventional operator-based edge detection approaches require additional postprocessing steps for the application. In the present study, in order to overcome this shortcoming, we have proposed the new ACS-based edge detection algorithm. The experimental results indicate that this proposed algorithm has the excellent performance in terms of robustness and flexibility.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.64-66
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• 2003

DNA(Deoxyribo Nucleic Acid)컴퓨팅은 생체분자를 계산의 도구로 이용하는 새로운 계산 방법으로 DNA 정보 저장능력과 DNA의 상보적인 관계를 이용하여 연산을 수행하는 방법이다. 최근에는 DNA 분자들이 갖는 강력한 병렬성을 이용하여 NP-Complete 문제에 적용하는 연구가 많이 시도되고 있다. Adleman이 DNA 컴퓨팅을 이용해 해결한 HPP(Hamilton Path Problem)와는 달리 TSP(Traveling Salesman Problem)는 간선에 가중치가 추가되었기 때문에 DNA 염기배열로 표현하기가 어렵고 또한 염기배열의 길이를 줄이기 위해 고정길이 염기배열을 사용할 경우 가중치가 커지면 효율적이지 못하다. 본 논문에서는 스무딩 알고리즘(smoothing algorithm)을 사용하여 간선의 가중치를 일정한 비율로 줄인 다음 유전자 알고리즘을 사용하여 최적의 염기배열을 찾는 방법을 제안하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.5
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• pp.1279-1288
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• 2007

A vehicle routing problem with time constraint is one of the must important problem in distribution and logistics. In practice, the service for a customer must start and finish within a given delivery time. This study is concerned about the development of a model to optimize vehicle routing problem under the multi-logistics center problem. And we used a two-step approach with an improved genetic algorithm. In step one, a sector clustering model is developed by transfer the multi-logistics center problem to a single logistics center problem which is more easy to be solved. In step two, we developed a GA-TSP model with an improved genetic algorithm which can search a optimize vehicle routing with given time constraints. As a result, we developed a Network VRP computer programs according to the proposed solution VRP used ActiveX and distributed object technology.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.447-448
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• 2013

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05a
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• pp.317-320
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• 2003

본 논문에서는 각 도시마다 가중치가 있는 City domain을 tour하기 위한 문제를 해결하기 위해 Simulated Annealing Algorithm을 확장한 알고리즘을 제시하였고 Capacitated vehicle routing problem을 변형한 Augmented multiple salesman traveling problem을 정의하고 이를 해결하기 위한 에너지 함수와 알고리즘을 제시하였다.