• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.5
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• pp.444-448
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• 2010

RCR network[1] is a topology for interconnection networks having many desirable properties for building scalable parallel machines. This had been analyzed by Hu and Cao[2] to deal with problems of disconnected graph, bisection width and diameter. We analyze some properties of RCR again and revise the condition for connected graph and network diameter. And we present an efficient algorithm for finding next node on a shortest path.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.399-405
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• 2002

Now days, it is based on GIS and GPS, it can search for the shortest path and estimation of arrival time by using the internet and cell phone to driver. But, even though good car navigation system does not create which is the shortest path when there average vehicle speed is 10 -20 Km. Therefore In order to reduce vehicle waiting time and average vehicle speed, we suggest optimal green time algorithm using fuzzy adaptive control , where there are different traffic intersection length and lane. In this paper, it will be able to forecast the optimal traffic Information, estimation of destination arrival time, under construction road, and dangerous road using internet.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.45-49
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• 2004

최적경로문제는 한 지점에서 다른 지점으로 이동할 때, 최소한의 비용으로 이동할 수 있는 경로를 찾는 문제를 의미하며, 최근 인터넷을 이용한 경로 안내 시스템에 적용되어 왔다. 이때, 보통 시간비용을 최소로 하는 경로를 제공하는 것이 일반적이다. 그러나 현실적으로 우리는 타인에게 어떠한 경로를 설명하거나 알려 줄 때, 인지도나 접근성이 높은 경로를 포함하는 경우가 많다. 이에 본 연구에서는 교통경로를 산출할 때 접근성이 높은 경로를 포함하여 경로를 구성하는 방안을 제시하였다 이를 구현하기 위해 건축, 도시공간에서 접근성 분석에 사용되고 있는 Space Syntax라는 방법론을 적용하였다. GIS 데이터 구조를 이용하기 위해 알고리즘을 일부 수정하였으며, 일반적으로 최단거리 산출에 많이 사용되고 있는 Dijkstra 알고리즘과 결합하여 구축하였다. 이렇게 구축된 알고리즘을 소규모의 교통 네트웍상에 적용하여 테스트하였다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.6
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• pp.189-197
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• 2012

In this paper, we propose an optimal path search algorithm that applies the received signal strength between a mobile device and a satellite. Because the common path search algorithm is only based on the shortest path search, it is difficult to provide stable multimedia services for the satellite mobile devices. The proposed algorithm provides the stable communication environment for the satellite mobile devices based on received signal strength. In Satellite communications, changes in the radio quality are severe depending on the receiving environment. Therefore, an accurate analysis of the receiving environment characteristics is very important for providing stable multimedia services of satellite communications. The causes of radio attenuation are atmosphere attenuation, vegetation attenuation and buildings attenuation. These factors were applied to analyze the received signal strength. The proposed algorithm can search the optimal path in urban for stable satellite multimedia services.

• 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.

• The KIPS Transactions:PartC
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• v.14C no.1 s.111
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• pp.87-94
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• 2007

In mobile ad hoc networks the most popular on demand routing protocols are the Dynamic Source Routing (DSR) protocol and the Ad hoc On demand Distance Vector (AODV) routing protocol. These and other representative standard routing protocols are designed to find and maintain only a single path. Whenever there is a link break on the active route, source node has to invoke a route discovery process from the beginning and it causes a lot of overhead. Multipath routing protocols, which can alleviate these problems by establishing multiple alternative paths between a source and a destination, are widely studied. In this paper we propose a node disjoint multipath discovery technique based on AODV local route discovery. This technique can find and build completely separated node disjoint multi paths from a source to a destination as many as possible. It will make routing more robust and stable.

• Journal of KIISE:Databases
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• v.36 no.5
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• pp.405-410
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• 2009

This paper proposes an efficient path finding scheme capable of searching the paths to k static objects from a given query point, aiming at both improving the legacy k-nearest neighbor search and making it easily applicable to the road network environment. To the end of improving the speed of finding one-to-many paths, the modified A* obviates the duplicated part of node scans involved in the multiple executions of a one-to-one path finding algorithm. Additionally, the cost to the each object found in this step makes it possible to finalize the k objects according to the network distance from the candidate set as well as to order them by the path cost. Experiment results show that the proposed scheme has the accuracy of around 100% and improves the search speed by $1.3{\sim}3.0$ times of k-nearest neighbor searches, compared with INE, post-Dijkstra, and $na{\ddot{i}}ve$ method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.12C
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• pp.1215-1227
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• 2002

This paper presents a genetic algorithmic approach to shortest path (SP) routing problem. Variable-length chromosomes (strings) and their genes (parameters) have been used for encoding the problem. The crossover operation that exchanges partial chromosomes (partial-routes) at positionally independent crossing sites and the mutation operation maintain the genetic diversity of the population. The proposed algorithm can cure all the infeasible chromosomes with a simple repair function. Crossover and mutation together provide a search capability that results in improved quality of solution and enhanced rate of convergence. Computer simulations show that the proposed algorithm exhibits a much better quality of solution (route optimality) and a much higher rate of convergence than other algorithms. The results are relatively independent of problem types (network sizes and topologies) for almost all source-destination pairs.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.300-309
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• 2003

The Japanese developed the first Car navigation system in 1981 with the advent of Honda, which was known as the car inertial navigation system. Now days, It is possible to search the shortest route to and from places and arrival time using the internet via cell phone to the driver based on GIS and GPS. However, even with a good navigation system, it losses the shortest route when there is an average speed of the vehicle being between S-15 kilometers. Therefore, in order to improve the vehicle waiting time and average vehicle speed, we are suggesting an optimal green time algorithm using fuzzy adaptive control, where there are different traffic intersection lengths, and lanes. In this paper, to be able to assist the driver and forecast the optimal traffic information with regards to the road conditions; dangerous roads, construction work and estimation of arrival time at their destination using internet.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.7
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• pp.870-874
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• 2018

In the worst maritime accidents, people should abandon ship, but ship structures are narrow and complex and operation takes place on rough seas, so escape is not easy. In particular, passengers on cruise ships are untrained and varied, making evacuation prospects worse. In such a case, the evacuation management of the crew plays a very important role. If a rescuer enters a ship at distress and conducts rescue activities, which zones represent the most effective entry should be examined. Generally, crew and rescuers take the shortest route, but if an accident occurs along the shortest route, it is necessary to select the second-best alternative. To solve this situation, this study aims to calculate evacuation routes using Q-Learning of Reinforcement Learning, which is a machine learning technique. Reinforcement learning is one of the most important functions of artificial intelligence and is currently used in many fields. Most evacuation analysis programs developed so far use the shortest path search method. For this reason, this study explored optimal paths using reinforcement learning. In the future, machine learning techniques will be applicable to various marine-related industries for such purposes as the selection of optimal routes for autonomous vessels and risk avoidance.