• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.80-87
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• 2022

Lack of sufficient battery capacity is one of the most important challenges impeding the development of wireless sensor networks (WSNs). Recent innovations in the areas of wireless energy transfer and rechargeable batteries have made it possible to advance WSNs. Therefore, in this article, we propose an energy-efficient charging of sensors in a WSN scenario. First, we have formulated the problem as an integer linear programming (ILP) problem. Then a utility function-based greedy algorithm named UGreedy/UF1 is proposed for solving the problem. Finally, the performance of UGreedy/UF1 is analyzed along with other baseline algorithms: UGreedy/UF2, 2-opt TSP, and Greedy TSP. The simulation results show that UGreedy/UF1 performs better than others both in terms of the deadline missing ratio of sensors and the total energy consumption of UAVs.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.1501-1502
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• 2010

DualCore 혹은 MultiCore 플랫폼의 보급에 따라 높은 시간복잡도를 갖는 응용들도 사용자의 컴퓨터나 단말에서 수행되어 다양한 서비스를 제공할 수 있게 되었다. 본 논문에서는 관광 스케줄을 효율적으로 결정하기 위한 다중목적지 방문 문제에 대해 이중 쓰레드에 기반한 서치 스페이스 탐색 알고리즘을 구현한다. 이는 Traveling Salesman Problem의 한 종류로서 O(n!) 시간 복잡도를 갖고 있으며 검색시의 독립성때문에 각 쓰레드는 병렬적으로 최적의 스케줄을 탐색할 수 있다. 또 현재까지 발견된 최적값을 기반으로 부분 경로의 비용이 이미 최적값을 넘는 경우는 하위 탐색을 제거하여 상당한 성능의 향상을 가져온다. 2.4 GHz Intel(R) Core DuoCPU와 3 GB 메모리로 구성된 플랫폼 상에서 구현된 서비스는 11개의 목적지에 대한 방문 스케줄을 생성함에 있어서 단일 쓰레드 버전은 14.196초, 이중 쓰레드 버전은 6.411초, 제약조건을 포함한 이중 쓰레드 버전은 0.14초에 최적의 스케줄을 찾아낼 수 있다.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.85-90
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• 2023

The Ant Colony System (ACS) is a variant of Ant colony optimization algorithm which is well-known in Traveling Salesman Problem. This paper proposed a hybrid method based on genetic algorithm (GA) and ant colony system (ACS), called GACS, to solve traffic routing problem. In the GACS, we use genetic algorithm to optimize the ACS parameters that aims to attain the shortest trips and time through new functions to help the ants to update global and local pheromones. Our experiments are performed by the GACS framework which is developed from VANETsim with the ability of real map loading from open street map project, and updating traffic light in real-time. The obtained results show that our framework acquired higher performance than A-Star and classical ACS algorithms in terms of length of the best global tour and the time for trip.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.8
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• pp.122-129
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• 1997

In this paper, we propose a Hopfield model for solving the part-matching in case that is the number of parts and positions are changed. The goal of this paper is to minimize part-connection in pairs and total path of part-connections. Therefore, this kind of problem is referred to as a combinatiorial optimization problem. First of all, we review the theoretical basis for Hopfield model and present two optimal algorithms of part-matching. The first algorithm is Traveling Salesman Problem(TSP) which improved the original and the second algorithm is Wdighted Matching Problem (WMP). Finally, we show demonstration through com- puter simulation and analyze the stability and feasibility of the generated solutions for the proposed con- nection methods. Therefore, we prove that the second algorithm is better than the first algorithm.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.1352-1354
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• 2008

2008년 7월 인터넷 기사에 "살인적 노동, 택배 배송직원의 하루"라는 글이 올라왔다. 하루 16시간을 뛰어 다녀야 하는 배송직원들은 자신이 배달하는 지역별로 차에 물건을 싣는 동시에 배송지역을 지도로 확인하는 작업까지 해야 한다. 그리고 배달경로 설정 또한 전적으로 그 지역 배송직원의 개인적인 노하우에 의존하여 이루어진다는 것이다. 본 연구에서는 물건의 배송정보가 RFID에 저장이 되어있다는 가정하에 지리정보시스템과 TSP(Traveling salesman problem)을 이용하여 차에 실려있는 물건의 배송지역을 디스플레이해주고 다수의 경유지를 최소 거리와 최소 시간에 방문할 수 있는 시스템을 제안한다.

• Journal of Korean Society of Transportation
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• v.23 no.4 s.82
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• pp.81-91
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• 2005

The Traveling Salesman Problem(TSP) is one of the NP-complete (None-deterministic Polynomial time complete) route optimization problems. Its calculation time increases very rapidly as the number of nodes does. Therefore, the near optimum solution has been searched by heuristic algorithms rather than the real optimum has. This paper reviews the Ant System Algorithm(ANS), an heuristic algorithm of TSP and its applicability in the parcel delivery service in Korea. ASA, which is an heuristic algorithm of NP-complete has been studied by M. Dorigo in the early 1990. ASA finds the optimum route by the probabilistic method based on the cumulated pheromone on the links by ants. ASA has been known as one of the efficient heuristic algorithms in terms of its calculation time and result. Its applications have been expanded to vehicle routing problems, network management and highway alignment planning. The precise criteria for vehicle routing has not been set up in the parcel delivery service of Korea. Vehicle routing has been determined by the vehicle deriver himself or herself. In this paper the applicability of ASA to the parcel delivery service has been reviewed. When the driver s vehicle routing is assumed to follow the Nearest Neighbor Algorithm (NNA) with 20 nodes (pick-up and drop-off places) in $10Km{\times}10Km$ service area, his or her decision was compared with ASA's one. Also, ASA showed better results than NNA as the number of nodes increases from 10 to 200. If ASA is applied, the transport cost savings could be expected in the parcel delivery service in Korea.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.10
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• pp.2357-2375
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• 2013

Message ferry is a controllable mobile node with large capacity and rechargeable energy to collect information from the sensors to the sink in wireless sensor networks. In the existing works, route of the message ferry is often designed from the solutions of the Traveling Salesman Problem (TSP) and its variants. In such solutions, the ferry route is often a simple cycle, which starts from the sink, access all the sensors exactly once and moves back to the sink. In this paper, we consider a different case, where the ferry route is a closed walk that contains more than one simple cycle. This problem is defined as the Closed Walk Ferry Route Design (CWFRD) problem in this paper, which is an optimization problem aiming to minimize the average weighted delay. The CWFRD problem is proved to be NP-hard, and the Integer Linear Programming (ILP) formulation is given. Furthermore, a heuristic scheme, namely the Initialization-Split-Optimization (ISO) scheme is proposed to construct closed walk routes for the ferry. The experimental results show that the ISO algorithm proposed in this paper can effectively reduce the average weighted delay compared to the existing simple cycle based scheme.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.3
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• pp.329-343
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• 1995

Traditionally, machining process sequence was influenced and constrained by the design information obtained from CAD data base, i.e., class of operations, geometric shape, tooling, geometric tolerance, etc. However, even though all the constraints from design information are considered, there may exist more than one way to feasibly machine parts. This research is focused on the integrated problem of operations sequencing and machine tools selection in the presence of the product mix and their production volumes. With the transitional costs among machining operations, the operation sequencing problem can be formulated as a well-known Traveling Salesman Problem (TSP). The transitional cost between two operations is expressed as the sum of total machining time of the parts on a machine for the first operation and transportation time of the parts from the first machine to a machine for the second operation. Therefore, the operation sequencing problem formulated as TSP cannot be solved without transitional costs for all operation pairs. When solved separately or serially, their mutual optima cannot be guaranteed. Machining operations sequencing and machine tool selection problems are two core problems in process planning for discretely machined parts. In this paper, the interrelated two problems are integrated and analyzed, zero-one integer programming model for the integrated problem is formulated, and the solution methods are developed using a Tabu Search technique.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1939-1943
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• 1991

Path planning is an important task for optimal motion of a robot in structured or unstructured environment. The goal of this paper is to plan the shortest collision-free path in 3D, when a robot is navigated to pick up some tools or to repair some parts from various locations. To accomplish the goal of this paper, the Path Coordinator is proposed to have the capabilities of an obstacle avoidance strategy[3] and a traveling salesman problem strategy(TSP)[23]. The obstacle avoidance strategy is to plan the shortest collision-free path between each pair of n locations in 2D or in 3D. The TSP strategy is to compute a minimal system cost of a tour that is defined as a closed path navigating each location exactly once. The TSP strategy can be implemented by the Neural Network. The obstacle avoidance strategy in 2D can be implemented by the VGraph Algorithm. However, the VGraph Algorithm is not useful in 3D, because it can't compute the global optimality in 3D. Thus, the Path Coordinator is proposed to solve this problem, having the capabilities of selecting the optimal edges by the modified Genetic Algorithm[21] and computing the optimal nodes along the optimal edges by the Recursive Compensation Algorithm[5].

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.49-60
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• 1999

This paper addresses a welding task sequencing for robot arc welding process planning. Although welding task sequencing is an essential step in the welding process planning, it has not been considered through a systematic approach, but it depends rather on empirical knowledge. Thus, an effective task sequencing for robot arc welding is required. Welding perations can be classified by the number of welding robots. Genetic algorithms are applied to tackle those welding task sequencing problems. A genetic algorithm for traveling salesman problem (TSP) is utilized to determine welding task sequencing for a MultiWeldline-SingleLayer problem. Further, welding task sequencing for multiWeldline-MultiLayer welding is investigated and appropriate genetic algorithms are introduced. A random key genetic algorithm is also proposed to solve multi-robot welding sequencing : MultiWeldline with multi robots. Finally, the genetic algorithm are implemented for the welding task sequencing of three dimensional weld plate assemblies. Robot welding operations conforming to the algorithms are simulated in graphic detail using a robot simulation software IGRIP.