• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.52
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• pp.97-107
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• 1999

The asymmetric traveling salesman problem is a representative NP-Complete problem. Polynomial algorithm for this problem has not been yet found. So, many heuristic methods have been researched in this problem. We need heuristic methods that produce good answers for some larger problems in reasonable times. 3-opt is well known for the effective local-search heuristic method. It has been used in many applications of the asymmetric traveling salesman problem. This paper discusses 3-opt's properties and ineffective aspects and presents a highly effective heuristic method. 3-opt does not consider good arcs(shorter distance or little cost). This paper presents a fast heuritic algorithm compared with 3-opt by inserting good arcs and deleting related arcs later.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11a
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• pp.323-326
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• 2002

DNA 컴퓨팅은 생체 분자들이 갖는 막대한 병렬성을 이용하여 조합 최적화 문제에 적용하는 연구가 많이 시도되고 있다. 특히 TSP(Travelling Salesman Problem)는 간선에 대한 가중치 정보가 추가되어 있기 때문에 가중치를 DNA 염기 배열로 표현하기 위한 효율저인 방법들이 제시되지 않았다. 따라서 본 논문에서는 DNA 컴퓨팅에 DNA 코딩 방법을 적용하여 정점과 간선을 효율적으로 생성하고 표현된 DNA 염기 배열의 간선에 실제간을 적용하여 가중치 정보를 계산하는 ACO(Algorithm for Code Optimization)를 제안한다. DNA 코딩 방법은 변형된 유전자 알고리즘으로 DNA 기능을 유지하며, 서열의 길이를 줄일 수 있으므로 최적의 서열을 생성할 수 있는 특징을 갖는다. 실험에서 ACO를 TSP에 적용하여 Adleman의 DNA 컴퓨팅 알고리즘과 비교하였다. 그 결과 초기 문제 표현에서 우수한 적합도 값을 생성했으며, 경로의 변화에도 능동적으로 대처하여 최적의 결과를 빠르게 탐색할 수 있었다.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10a
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• pp.744-746
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• 1998

외판원(Traveling Salesman Problem)는 계산 복잡도가 매우 높으므로 이를 해결하려는 다양한 방법들이 제시되어 왔다. 최근에는 특히 휴리스틱(Heuristic) 에 기반한 유전 알고리즘(Genetic Algorithm)에 위한 방법이 관심을 집중시키고 있고, 이를 위한 다양한 교잡(Crossiver)연산자와 돌연변이(Mutation) 연산자들이 발표되고 있다. 돌연변이연산자는 지역해에 빠지는 것을 방지하며, 유용한 유전 특성을 잃어버릴 위험이 있는 교잡 연산자의 단점을 보완할 수 있다. 본 논문에서는 새로운 돌연변이 연산자를 개발하여 적용한 유전 알고리즘으로 외판원 문제를 해결한다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.354-366
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• 1993

In this paper, new algorithms for solving the multiple traveling salesman problem with time windows are presented. These algorithms are based on the flow based algorithms for solving the vehicle scheduling problem. Computational results on problems up to 750 customers indicate that these algorithms produce superior results to existing heuristic algorithms for solving the vehicle routing problems when the time windows are 'tight enough' where 'tight enough' is based on a metric proposed by desrosiers et al.(1987).

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.2
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• pp.105-130
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• 1993

This study deals with finding a schedule for the movement of a material handling device (elevator) in a manufacturing plant. Two different algorithm (Traveling Salesman Technique and Greedy Algorithm) are used in the scheduling of the elevators using a simulation technique to determine the proper method of scheduling the elevator movement. Based on the simulation analysis, we have found that the Greedy algorithm serves better than the algorithm based on Traveling Salesman technique for scheduling the movement of a material handling device in the manufacturing plant.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.51
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• pp.21-28
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• 1999

The TSP(Traveling Salesman Problem) is one of the most widely studied problems in combinatorial optimization. The most common interpretation of TSP is finding a shortest Hamiltonian tour of all cities. The objective of this paper proposes a new heuristic algorithm MCH(Multi-Convex hulls Heuristic). MCH is a algorithm for finding good approximate solutions to practical TSP. The MCH algorithm is using the characteristics of the optimal tour. The performance results of MCH algorithm are superior to others algorithms (NNH, CCA) in CPU time.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.652-656
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• 2002

본 연구에서는 각 수요지간의 시간이 확률적으로 주어지는 경우의 TSP(Traveling Salesman Problem)를 다루고자 한다. 현실적으로, 도심의 교통 체증 등으로 인해서 각 지점간의 걸리는 시간은 시간대별로 요일별로 심한 변화를 일으키기 마련이다. 그러나, 현재까지의 연구 결과는 수요지간의 경과시간이 확정적으로 주어지는 경우가 대부분으로, 도심물류 등에서 나타나는 현실적인 문제를 해결하는데는 많은 한계가 있다 본 연구에서는 문제의 해법으로 강화학습기법의 하나인 Q학습(Q-Learning)과 Neural Network를 활용한 효율적인 알고리즘을 제시한다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.33
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• pp.111-118
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• 1995

This paper suggests a hybrid genetic algorithm for asymmetric traveling salesman problem(TSP). The TSP was proved to be NP-complete, so it is difficult to find optimal solution in reasonable time. Therefore it is important to develope an algorithm satisfying robustness. The algorithm applies dynamic programming to find initial solution. The genetic operator is uniform order crossover and scramble sublist mutation. And experiment of parameterization has been performed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.249-257
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• 2015

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.

• Spatial Information Research
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• v.11 no.3
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• pp.275-289
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• 2003

This study focused on offering a helpful information for the touring. To develop a tour route guidance tool, it is needed to use a GIS function, which can suggest a possible shortest path based on time and distance. A Traveling salesman problem algorithm, which was developed to solve multi destination problem in network analysis, was used to implement a tour guidance system. This system was developed using ArcObjects programming components within ArcGIS 8.3. Jeju city was selected for the case study to apply the tool and to test the effectiveness of it. This study demonstrated that this tool was considerably effective for finding a probable optimum tour path in the following aspects. First, it can help tourists to select several attractions from numerous tour sites in an area given limited time. Second, tourist can manage time efficiently by organizing their tour courses on the basis of the tool. Third, tourists can reduce the uncertainties that may happen under unexpected situations in unfamiliar places by obtaining specific spatial information using the tool. Fourth, the Graphic User Interface of the tool can be easily used to obtain visual information of spatial data.