• Journal of KIISE:Computer Systems and Theory
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• v.34 no.5_6
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• pp.195-201
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• 2007

A minimum terminal path decomposition of a tree is defined as a partition of the tree into edge-disjoint terminal-to-terminal paths that minimizes the weight of the longest path. In this paper, we present an $O({\mid}V{\mid}^2$time algorithm to find a minimum terminal path decomposition of trees. The algorithm reduces the given optimization problem to the binary search using the corresponding decision problem, the problem to decide whether the cost of a minimum terminal path decomposition is at most l. This decision problem is solved by dynamic programing in a single traversal of the tree.

• Journal of the military operations research society of Korea
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• v.33 no.2
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• pp.31-47
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• 2007

The main purpose of this study is to find out the best solution of the vehicle routing problem with hard time window by using both genetic algorithm and heuristic. A mathematical programming model was also suggested in the study. The suggested mathematical programming model gives an optimal solution by using ILOG-CPLEX. This study also suggests a hybrid genetic algorithm which considers the improvement of generation for an initial solution by savings heuristic and two heuristic processes. Two heuristic processes consists of 2-opt and Or-opt. Hybrid genetic algorithm is also compared with existing problems suggested by Solomon. We found better solutions rather than the existing genetic algorithm.

• Science of Emotion and Sensibility
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• v.17 no.2
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• pp.111-122
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• 2014

This study has analyzed the scanning path algorithm shown at the process of exploring spatial information through an observation experiment with the object of lobby in subway station. In the estimation of observation time by section, the frequency of scanning type was found to increase as the observation time got longer, which makes it possible that the longer the observation lasts the more the observation interruptions occur. In addition, the observation slipped out of the range of imaging when any fatigue was caused from the observation or the more active exploration took place. Furthermore, when the trend line was employed for the examination of the changes to the scanning type by time section, "concentration" "diagonal or vertical" showed a sharp and a gentle increases along with the increase of time section respectively, while "circulation. combination, horizontal" showed a reduction. The observation data of the subjects observing a space include various visual information. The analysis of the scanning type found at "attention concentration" enabled to draw this significant conclusion. The features of increase and decrease of scanning types can be a fundamental data for understanding the scanning tendency by time.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.526-529
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• 2000

본 연구는 물류 개선이 시급하고, 전자상거래 등으로 인한 물류 거점의 확보가 중요시되고 있는 현실의 문제점을 개선하기 위해 Simulated Annealing 알고리즘을 제안한다. 이미 위치가 설정된 노드의 요구에 최소비용으로 원활히 대응하기 위한 다 물류센터의 최적 위치와 할당영역, 규모를 결정하고, 각 물류센터가 담당한 영역의 노드를 반드시 한번씩 경유하여 처음 위치로 돌아오는 최소비용의 경로를 탐색한다. 이러한 과정을 위해 두 개의 모델인 1) 다 물류센터의 위치결정을 통한 규모결정과 영역할당모델, 2) 경로계획 모델을 개발한다. 거리산정방법과 물동량에 따른 가중치를 적용한 다양한 물류센터의 위치결정과 규모결정, 각 물류센터별 영역을 할당하여 단 물류센터의 문제로 만든 후 경로계획을 실시하여 최소비용의 경로(Tour)를 구하는 알고리즘을 개발하고 Sample을 적용한다.

• 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 Advanced Navigation Technology
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• v.13 no.5
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• pp.646-655
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• 2009

This paper presents a new search strategy based on models of evolution in order to solve the problem of collision-free robotic path planning. We designed the robot path planning method with genetic algorithm which has become a well-known technique for optimization, intelligent search. Considering the path points as genes in a chromosome will provide a number of possible solutions on a given map. In this case, path distances that each chromosome creates can be regarded as a fitness measure for the corresponding chromosome. The effectiveness of the proposed genetic algorithm in the path planning was demonstrated by simulation. The proposed search strategy is able to use multiple and static obstacles.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.2
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• pp.89-95
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• 2002

Global routing is to assign each net to routing regions to accomplish the required interconnections. The most popular algorithms for global routing inlcude maze routing algorithm, line-probe algorithm, shortest path based algorithm, and Steiner tree based algorithm. In this paper we propose weighted network heuristic(WNH) as a minimal Steiner tree search method in a routing graph and a genetic algorithm based on WNH for the global routing. We compare the genetic algorithm(GA) with simulated annealing(SA) by analyzing the results of each implementation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.11A
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• pp.1164-1172
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• 2007

To solve scalability problem in the ZigBee Network, this paper presents a new mesh routing protocol for ZigBee, called ZigBee Cluster Label (ZiCL). ZiCL divides the ZigBee network into one or more logical clusters and then assigns a unique Cluster Label to each cluster so that it discovers a route of a destination node based on Cluster Label. When a node collects new Cluster Label information of a destination node according to discovery based on Cluster Label, ZiCL encourages nodes with the same Cluster Label to share the information. Consequen tly, it contributes on reducing numerical potential route discoveries and improving network performances such as routing overhead, end-to-end delay, and packet delivery ratio. Simulation results using NS-2 show ZiCL performs well.

• Journal of Korea Spatial Information System Society
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• v.4 no.1 s.7
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• pp.27-37
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• 2002

Ideas providing an optimal car route using current traffic condition, maintaining the current location and the history of driven route of a car in the main central office, in where GPS signals transmitted from the driving cars are received, have been proposed. Since GPS signals occurred in certain time interval instead of all GPS signals are transmitted from the car due to the cost of transmission, an algorithm that is able to recover the missing GPS signals is required. In this paper, an efficient algorithm, which finds the driven route and the current location of a car fast, is proposed. To verify the efficiency of the proposed algorithm, it is applied to the various real GIS map and it turns out to be very effective.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.4
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• pp.361-365
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• 2002

오랜 세월동안 위대한 이동수단을 만들어내고자 하는 인간의 꿈은 오늘날 눈부신 각종 운송기구를 만들어 내는 결실을 얻고 있다. 자동차 네비게이션 시스템도 그러한 결실중의 한 예라고 할 수 있을 것이다. 지능적으로 판단하고 정보를 처리할 수 있는 자동차 네비게이션 시스템을 부착함으로써 한 단계 발전한 운송수단으로 진화할 수 있을 것이다. 이러한 자동차 네비게이션 시스템의 단점이라면 한정된 리소스만으로 여러 가지 작업을 수행해야만 하는 어려움이다. 그래서 네비게이션 시스템의 주요 작업중의 하나인 경로를 추출하는 경로추출(Route Planning) 작업은 한정된 리소스에서도 최적의 경로를 찾을 수 있는 지능적인 방법이어야만 한다. 이러한 경로를 추출하는 작업을 하는데 기존에 일반적으로 쓰였던 두 가지 방법에는 Dijkstra s algorithm과 A*algorithm이 있다. 이 두 방법은 최적의 경로를 찾아낸다는 점은 있지만 경로를 찾기 위해서 알고리즘의 특성상 각각, 넓은 영역에 대하여 탐색작업을 해야 하고 또한 수행시간이 많이 걸린다는 단점과 또한 경로를 계산하기 위해서 Heuristic function을 추가적인 정보로 계산을 해야 한다는 단점이 있다. 본 논문에서는 적은 탐색 영역을 가지면서 또한 최적의 경로를 추출하는데 드는 수행시간은 작으며 나아가 동적인 교통환경에서도 최적의 경로를 추출할 수 있는 최적 경로 추출방법을 강화학습의 일종인 Q- Learning을 이용하여 구현해 보고자 한다.