• Journal of Advanced Navigation Technology
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• v.19 no.2
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• pp.116-122
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• 2015

Motivated by continuous increase in flight demand, awareness of the importance in developing ways to increase aircraft operational efficiency on the airport movement area has been raised. This paper proposes a new routing algorithm for providing the shortest path in a right time, enhancing the aircraft movement efficiency. Many researches on developing algorithms have been performed, for example, Dijkstra algorithm and $A^*$ algorithm. The Dijkstra algorithm provide optimal solution but could possibly provide it with a cost of relatively longer computation time. On the other hand, $A^*$ algorithm does not guarantee the optimality of a solution. In this paper, we suggest a Hybrid $A^*$ algorithm, incorporating both algorithms to eliminate the weaknesses. Rigorous test shows the proposed Hybrid $A^*$ algorithm may achieve shorter computing time and optimality in searching the shortest path.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.195-201
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• 2010

Recently, the necessity of the autonomous mobile robot is emphasized in order to enlarge the scope of activity and actively cope with the change of work environment. This paper proposes the algorithm which enables the mobile robot to avoid obstacles and lead it to the destination by the shortest path. And we verify the usability by a simulation. We made the algorithm with micro-GA and $\lambda$-geometry MRA. The area of simulation is limited to 320(width)$\times$200(length) pixels and one pixel is one centimeter. When we planned the path with only $\lambda$-geometry MRA, we could find the direction for path planning but could not find the shortest path. But when we planned the path with $\lambda$-geometry MRA and micro-GA, we could find the shortest path. So the algorithm enables us to find the direction for path planning and the shortest path.

• Journal of the Korea Society of Computer and Information
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• v.20 no.4
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• pp.25-32
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• 2015

The Genetic algorithm is a search algorithm using evaluation, genetic operator, natural selection to populational solution iteratively. The convergence and divergence characteristic of genetic algorithm are affected by selection strategy, generation replacement method, genetic operator when genetic algorithm is designed. This paper proposes fast convergence genetic algorithm for time-limited robot path planning. In urgent situation, genetic algorithm for robot path planning does not have enough time for computation, resulting in quality degradation of found path. Proposed genetic algorithm uses fast converging selection strategy and generation replacement method. Proposed genetic algorithm also uses not only traditional crossover and mutation operator but additional genetic operator for shortening the distance of found path. In this way, proposed genetic algorithm find reasonable path in time-limited situation.

• Journal of KIISE:Information Networking
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• v.35 no.6
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• pp.521-528
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• 2008

Such conventional maritime communication technologies as radio have short some comings in their transmission quality. It can be overcome by wireless channels provided by satellites such as INMARSAT, which nevertheless suffer from the high costs. In this paper, we propose a novel technology resolving the above problems, featuring in the establishment of maritime communication networks with multi-hop structures. The inter vessel and ship-to- shore networks previously modeled after MANET are remodeled by SANET (Ship Ad Hoc Networks) in the present work. Fan-shaped Search Zone Routing (FSR) protocol also is presented, which utilizes not only static geographical information including the locations of ports and the navigations of courses but also the unique characteristics of ships in terms of mobile nodes. The FSR finds the fan-shaped search zone on which the shortest path is located. The performance of LAR protocol is compared with that of FSR in several ways. First, FSR does not make use of a type of control packets as beaconing data, resulting in a full utilization of the bandwidth of the wireless channels. Second, the delivery rate by the FSR is 100% for the fan-shaped search zone includes at least one route between source and destination nodes on its border line, where as that of LAR has been turned out to be 64%. Third, the optimality of routes searched by the FSR is on a 97% level. Of all, the FSR shows a better performance than LAR by about 50%.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.2
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• pp.268-275
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• 2011

This paper proposes two optimal path planning methods of a mobile robot using uDEAS (univariate Dynamic Encoding Algorithm for Searches). Before start of autonomous traveling, a self-controlled mobile robot must generate an optimal global path as soon as possible. To this end, numerical optimization method is applied to real time path generation of a mobile robot with an obstacle avoidance scheme and the basic path generation method based on the concept of knot and node points between start and goal points. The first improvement in the present work is to generate diagonal paths using three node points in the basic path. The second innovation is to make a smooth path plotted with the blending polynomial using uDEAS. Effectiveness of the proposed schemes are validated for several environments through simulation.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.351-356
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• 2022

Among the path planning methods used to generate the ship's path, the graph search-based method is widely used because it has the advantage of its completeness, optimality. In order to apply the graph-based search method to the berthing path plan, the deviation from the path must be minimized. Path following suitability should be considered essential, since path deviation during berthing can lead to collisions with berthing facilities. However, existing studies of graph search-based berthing path planning are dangerous for application to real-world navigation environments because they produce results with a course change just before berthing. Therefore, in this paper, we develop a cost function suitable for path following, and propose a 3D A* algorithm that applies it. In addition, in order to evaluate the suitability for the actual operating environment, the results of the path generation of the algorithm are compared with the trajectory of the data collected by manned operations.

• 한국도로학회:학술대회논문집
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• 2010.09a
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• pp.229-234
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• 2010

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.729-731
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• 2016

The efficiency of genetic algorithm may be improved, as genetic generation increases. However, a number of algorithms are needed until desired results are obtained. In addition, if Hoc unit increases when linked to a network, there may be a need to compare with all the cases, which would result in many algorithms at a time, and if a single process deals with such algorithms, the efficiency will decrease. Therefore, efficiency of overall network will be decreased in the end. Proposal algorithm in this thesis introduced cells, units of router group, for distributed processing of previous genetic algorithm. This thesis presented ways to reduce search delay time of overall network through cell-based genetic algorithm.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06d
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• pp.367-372
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• 2008

최근 사용자들의 특성에 맞게 개인화되고 세분화된 위치 기반 서비스를 개발하기 위한 목적으로 이동 객체의 다양한 패턴들 중 의미있는 지식인 유용한 이동 패턴을 탐사하는 문제가 주요 이슈로 부각되고 있다. 이에 본 논문에서는 방대한 이동 객체의 이력 데이터 집합으로부터 특정 지점들 간의 최적 이동 경로나 정해진 시간내의 스케줄링 경로 탐색과 같이 복합적인 시간 및 공간 제약을 갖는 최적 이동 패턴을 탐사하는 문제에 대해 정의하고, 다양한 이동 패턴들 중 가장 빈발하게 발생하는 패턴이 최적의 비용을 소요할 것이라는 가정을 기반으로 최대 빈발 2-시퀀스를 추출하는 방법을 제안한다. 후보 시퀀스 집합으로부터 지지도 계산을 통해 추출되는 빈발 2-시퀀스들의 순차적인 조합은 패턴 탐사를 수행하는 각 패스 진행 시 후보 시퀀스 항목의 차수가 점차 감소하여 최적 이동 패턴 탐사 방법에 효과적으로 적용된다.

• Journal of Korean Society of Transportation
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• v.34 no.6
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• pp.570-579
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• 2016

This study proposes a concept of Stepwise Transfer Coefficient(STC) which implies greater transfer cost with increasing the number of transfers. Thus, the public transport information system provides the choice sets of travel routes by the consideration of not only transportation time but also the optimum number of transfers. However, path choice problems that involve STC are found to include non additive cost, which requires additional route enumeration works. Discussions on route enumeration in actual transportation networks is very complicated, thereby warranting a theoretical examination of route search considering STC. From these points of view, this study results in a probability based transit trip assignment model including STC. This research also uses incoming link based entire route deletion method. The entire route deletion method proposed herein simplifies construction of an aggregation of possible routes by theoretically supporting the process of enumeration of the different routes from origin to destination. Conclusively, the STC reflected route based logit model is proposed as a public transportation transit trip assignment model.