• 한국인터넷방송통신학회논문지
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• 제10권5호
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• pp.215-221
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• 2010

홉필드 네트웍은 패턴 매칭과 더불어 최적화 문제를 푸는 도구로 사용될 수 있다. 특히 Zhang과 Ali는 홉필드 네트웍의 노드를 2차원으로 확장하여 최적화 문제를 해결하였다. 잠재적 브랜치의 총합인 노드의 제곱만큼 뉴런이 필요한 Ali 알고리즘은 탐색 네트워크가 커지면 많은 시간이 소요되는 단점이 있다. 본 논문에서는 Ali의 방식을 개선하여 계산량을 대폭 줄이고 효과적으로 최적 경로를 탐색할 수 있는 방식을 제안한다. 효과적인 최적 경로 탐색을 위하여 2단계로 구분하여 진행된다. 1단계에는 홉필드 네트웍을 2단계에는 eSPN 알고리즘을 사용하여 최적 경로를 탐색할 수 있다. 제안된 방식은 샘플 네트웍을 통하여 최적 경로 탐색이 확인되었으며, Ali 알고리즘보다 빠르고 간단하여 실제 최적화에 적용하기기 용이하다. 특히, 네트웍의 브랜치 비용이 변화할 경우에도 홉필드 네트웍의 연결 시냅스가 아닌 입력 바이어스를 조정하므로 동적으로 변화하는 네트웍의 최적 경로 탐색에도 유용하다.

• 한국통신학회논문지
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• 제21권5호
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• pp.1193-1199
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• 1996

This paper introduces an algorithm which uses MUIO and the shortest paths to minimize the length of test sequence. The length of test sequence is equal to the total number of the edges in a symmetric test graph $G^{*}$. Therefore, it is important to make a $G^{*}$ with the least number of the edges. This algorithm is based on the one proposed Shen[2]. It needs the complexity to make shortest paths but reduces the thest sequence by 1.0~9.8% over the Shen's algorithm. and this technique, directly, derives a symmetric test graph from an FMS.

• 전자공학회논문지B
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• 제30B권4호
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• pp.27-36
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• 1993

This paper proposes a shortest path allocation algorithm over the processors on the hypercube system based on the message passing techniques with the optimized module allocation. On multiprocessor systems, how to divide one task into multiple tasks efficiently is an important issue due to the hardness of the life cycle estimation of each process. To solve the life cycle discrepancies, the appropriate task assignment to each processor and the flexible communications among the processors are indispensible. With the concurrent program execution on hypercube systems, each process communicaties to others with the method of message passing. And, each processor has its own memory. The proposed algorithm generates a callable tree out of the module, assigns the weight factors, constructs the allocation graph, finds the shortest path allocation tree, and maps them with hypercube.

• 한국정보처리학회논문지
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• 제6권3호
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• pp.633-640
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• 1999

Reinforcement learning performs learning through interacting with trial-and-error in dynamic environment. Therefore, in dynamic environment, reinforcement learning method like Q-learning and TD(Temporal Difference)-learning are faster in learning than the conventional stochastic learning method. However, because many of the proposed reinforcement learning algorithms are given the reinforcement value only when the learning agent has reached its goal state, most of the reinforcement algorithms converge to the optimal solution too slowly. In this paper, we present COMREL(COMpressed REinforcement Learning) algorithm for finding the shortest path fast in a maze environment, select the candidate states that can guide the shortest path in compressed maze environment, and learn only the candidate states to find the shortest path. After comparing COMREL algorithm with the already existing Q-learning and Priortized Sweeping algorithm, we could see that the learning time shortened very much.

• 스마트미디어저널
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• 제7권2호
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• pp.9-14
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• 2018

The k-ary n-cube $Q^k_n$ is widely used in the design and implementation of parallel and distributed processing architectures. It consists of $k^n$ identical nodes, each node having degree 2n is connected through bidirectional, point-to-point communication channels to different neighbors. On $Q^k_n$ we would like to transmit packets from a source node to 2n destination nodes simultaneously along paths on this network, the $i^{th}$ packet will be transmitted along the $i^{th}$ path, where $0{\leq}i{\leq}2n-1$. In order for all packets to arrive at a destination node quickly and securely, we present an $O(n^3)$ routing algorithm on $Q^k_n$ for generating a set of one-to-many node-disjoint and nearly shortest paths, where each path is either shortest or nearly shortest and the total length of these paths is nearly minimum since the path is mainly determined by employing the Hungarian method.

• Journal of Communications and Networks
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• 제4권3호
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• pp.246-255
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• 2002

Constrained minimum Steiner tree (CMST) problem is a key issue in multicast routing with quality of service (QoS) support. Bounded shortest path algorithm (BSMA) has been recognized as one of the best algorithms for the CMST problem due to its excellent cost performance. This algorithm starts with a minimumdelay tree, and then iteratively uses a
-shortest-path (KSP) algorithm to search for a better path to replace a “superedge” in the existing tree, and consequently reduces the cost of the tree. The major drawback of BSMA is its high time complexity because of the use of the KSP algorithm. For this reason, we investigate in this paper the possibility of more efficient implementations of BSMA by using different methods to locate the target path for replacing a superedge. Our experimental results indicate that our methods can significantly reduce the time complexity of BSMA without deteriorating the cost performance.

• 대한교통학회지
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• 제22권4호
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• pp.135-146
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• 2004

교통정보에 의한 교통량분산 효과를 실질적으로 얻기 위해서는 좌회전금지, U-turn, P-turn과 같은 교차로내 회전제약이 존재하는 일반 가로망에서 적정수의 경로를 도출하여 제공해야 한다. 이를 위하여 k-path 알고리듬이 주로 이용되고 있으나 도출된 경로들간에 중복성이 문제가 되고 있다. 본 연구는 교차로내 회전제약들을 고려하면서 교통정보제공을 위한 n개의 최단경로탐색(n-path) 알고리듬을 개발하는 데 연구의 목적이 있다 여기서 n-path 알고리듬은 기존 k-path 알고리듬과는 차이가 있는데, k-path 알고리듬은 기종점간 통행비용을 기초로 첫 번째 최단경로외 2번째 최단경로, 3번째 최단경로,....식으로 k개의 최단경로를 찾는 데 비해, n-path 알고리듬은 각 경로간 일정수준 이상의 경로중첩(path overlap)이 발생하지 않도록 하면서 n개의 경로를 탐색하는 방법이다. 이를 위하여 첫 번째 탐색된 경로를 중심으로 통행비용과 경로중복수준을 판단하여 이후 경로들을 탐색하게 된다. 또한, 본 연구에서 제시하는 n-path 알고리듬은 기존 연구와는 달리 교차로상 회전제약을 반영하기 위하여 가로망을 확장할 필요가 없다는 장점이 있다. 개발된 알고리듬을 몇 개의 예제 네트워크에 적용하여 평가하였으며 평가결과 원하는 결과를 도출하고 있음을 확인할 수 있었다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.184-186
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• 2006

We propose a new method for shortest path planning of mobile robots. The topological information of the graph is obtained by thinning method to generate the collision-free path of robot. And the travelling path is determined through hierarchical planning stages. The first stage generates an initial path by use of Dijkstra's algorithm. The second stage then generates the final path by use of dynamic programming (DP). The DP adjusts the intial path to reduce the total travelling distance of robot. Simulation results are presented to verify the performance of the proposed method.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.591-595
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• 1998

This paper proposes a new concept of optimal shortest path algorithm which reduce average vehicle wating time and improve average vehicle speed, Electro sensitive traffic system can extend the traffic cycle when three are many vehicles on the road or it can reduce the traffic cycle when there are small vehicles on the road. But electro sensitive traffic light system doesn't control that kind of function when the average vehicle speed is 10km -20km. Therefore, in this paper to reduce vehicle waiting time we developed design of traffic cycle software tool that can arrive destinination as soon as possible using optimal shortest pass algorithm. Computer simulation result proved 10%-32% reducing average vehicle wating time and average vehicle speed which can select shortest route using built in G.P.S. vehicle is better than not being able to select shortest route function.

• 한국국방경영분석학회지
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• 제16권2호
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• pp.105-117
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• 1990

In the transportation network problems, it is often more desirable to select multiple number of optimal parths to prepare for additional constratints being imposed than to choose single optimal path. This paper addresses 'the problem of finding the k-shortest paths visiting p-specified nodes in a network'. The solution method is derived and the example of application is shown. The keypoint for determining the k-shortest paths via p-specified nodes is to combine the Shier's k-shortest path algorithm and the principle of optimality of dynamic programming method. Finally, for a transportation network problem consisting of national main routes, the k-shortest paths via some specified cites are obtained by using the solution method developed here.