• Proceedings of the Korean Society of Computer Information Conference
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• 2010.07a
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• pp.103-107
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• 2010

게임이나 네비게이션 시스템, 관광경로 설계에 있어서 경로찾기는 매우 중요한 부분 중의 하나이다. 일반적으로 TSP(Traveling Salesman Problem), RPP(Rural Postman Problem), CPP(Chinese Postman Problem)와 같은 경로찾기 문제들은 일반적인 알고리즘으로 최적해를 구할 수 없다. 문제크기가 커질수록 해집합이 폭발적으로 커짐으로써 전체 해집합을 탐색하는데 많은 비용이 든다. 따라서, 이러한 문제들은 유전알고리즘이나 Simulated Annealing과 같은 휴리스틱 알고리즘을 이용하여 근사최적 경로를 찾는다. 본 논문에서는 이와 같은 경로찾기 문제의 근사 최적해를 구하기 위한 시뮬레이션 시스템을 설계하고 구현하였다. 본 연구에서 구현한 시뮬레이션 시스템에는 유전알고리즘 엔진(GA 엔진)과 사용자 인터페이스를 제공한다. 사용자 인터페이스는 유전알고리즘에 사용될 파라미터를 설정하는 부분이며, GA 엔진은 유전알고리즘의 연산자들을 제공하는 부분이다. 본 논문에서 구현한 시뮬레이션 시스템은 게임과 같은 경로찾기 등에 활용될 수 있다.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2342-2344
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• 1998

In this paper, the path planner is presented for a robot to achieve an efficient path forward the given goal position in two dimensional environment which is involved with partially unknown obstacles. The path planner consists of three major components: off-line path planning, on-line path planning, and modification of planned path. Off-line path planning is based on known environment and creates the shortest path. On-line path planning is for finding unknown obstacles. The modification can be accomplished, by genetic algorithm, to be smooth path for preventing slippage and excessive centrifugal force.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.10a
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• pp.182-187
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• 2008

It needs to consider of turns during a path-finding on real road network. traveling on real road network, it generally takes less travel time in a more straight path than a zig-zaged path with same source and destination. In this paper, we propose $VTA^*$ algorithm that can reduce the cost of exploring despite increasing the number of turn in comparing with $TA^*$ algorithm. We have implement the proposed $VTA^*$, $TA^*$ which consider the number of turn and a traditional $A^*$ algorithm which dosen't consider the number of turn. The experimental result shows that the cost of exploring is reduced by 7.31 % comparing with $TA^*$ and the number of turn is reduced by 27.95% comparing with $A^*$ approximately.

• Journal of KIISE
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• v.43 no.9
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• pp.1026-1033
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• 2016

Path-finding on a grid map is a problem generally addressed in the fields of robotics, intelligent agents, and computer games. As technology advances, virtual game worlds tend to be represented more accurately and more realistically, resulting in an excessive increase in the number of grid tiles and in path-search time. In this study, we propose a path-finding algorithm that allows a prompt response to real-time queries by constructing a reduced state space and by precomputing all possible paths in an offline preprocessing stage. In the preprocessing stage, we vertically decompose free space on the grid map, construct a connectivity graph where nodes are the decomposed regions, and store paths between all pairs of nodes in matrix form. In the real-time query stage, we first find the nodes containing the query points and then retrieve the corresponding stored path. The proposed method is simulated for a set of maps that has been used as a benchmark for grid-based path finding. The simulation results show that the state space and the search time decrease significantly.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.3
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• pp.273-282
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• 2016

There has been growing social interest recently in the movement rights of people with reduced mobility. However, it simply eliminates the temporary inconvenience of walking of people with reduced mobility because it focuses only on supply of institutional facilities. Therefore, we look forward to improving movement welfare by proposing an optimized path finding algorithm for people with reduced mobility that takes into consideration physical elements affecting their movement, such as slope, steps etc. We selected Walking barrier factor by analyzing previous studies and calculated the relative importance of Walking barrier factors using an Analytic Hierarchy Process(AHP). Next, through the fuzzy system, the Walking disturbance level of link, which integrates the weights of Walking barrier factors and the attributes of each link, is derived. Then, Walking path cost that takes into consideration the ‘length’ factors is calculated and an optimized path for people with reduced mobility is searched using Dijkstra’s Algorithm. Nineteen different paths were searched and we confirmed that the derived paths are meaningful in terms of improving the mobility of people with reduced mobility by conducting a field test. We look forward to improving movement welfare by providing a navigation service using the path finding algorithm proposed in this study.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.4
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• pp.97-104
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• 2018

In the conventional direction finding, the antenna is installed at a high position on the ground to detect the position of the target with the environment of the LOS(Line of Sight) as much as the signal receiving environment. However, in order to configure such environment, high cost and installation time were required. In this paper, we use TDOA(Time Difference of Arrival) technique to utilize drones in direction finding, so that four drones can be used for directions finding simulation. Simulations based on drone and TDOA direction finding were constructed using additional signal processing Taylor series and Exact Interactive Algorithm. In the simulation, the receiving power is defined by using the 800MHz path-loss model using the GPS information of the ground direction detection, and the position estimation performance is analyzed when the TDOA technique, the Taylor series, and the Exact Interactive Alogrithm are applied.

• Journal of Distribution Science
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• v.14 no.2
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• pp.41-45
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• 2016

Purpose - Finding an optimal path is an essential component for the design and operation of smart transportation or logistics network. Many applications in navigation system assume that travel time of each link is fixed and same. However, in practice, the travel time of each link changes over time. In this paper, we introduce a new transportation problem to find a latest departing time and delivery path between the two nodes, while not violating the appointed time at the destination node. Research design, data, and methodology - To solve the problem, we suggest a mathematical model based on network optimization theory and a backward search method to find an optimal solution. Results - First, we introduce a dynamic transportation problem which is different with traditional shortest path or minimum cost path. Second, we propose an algorithm solution based on backward search to solve the problem in a large-sized network. Conclusions - We proposed a new transportation problem which is different with traditional shortest path or minimum cost path. We analyzed the problem under the conditions that travel time is changing, and proposed an algorithm to solve them. Extending our models for visiting two or more destinations is one of the further research topics.

• IE interfaces
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• v.21 no.1
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• pp.1-7
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• 2008

In this paper we study the Minimum Edge Addition Problem(MEAP) to decrease the diameter of a graph. MEAP can be used for improving the serviceability of telecommunication networks with a minimum investment. MEAP is an NP-hard optimization problem. We present two mathematical programming models : One is a multi-commodity flow formulation and the other is a path partition formulation. We propose a branch-and-price algorithm to solve the path partition formulation to the optimality. We develop a polynomial time column generation sub-routine conserving the mathematical structure of a sub problem for the path partition formulation. Computational experiments show that the path partition formulation is better than the multi-commodity flow formulation. The branch-and-price algorithm can find the optimal solutions for the immediate size graphs within reasonable time.

• International Journal of Control, Automation, and Systems
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• v.4 no.1
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• pp.96-104
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• 2006

We propose a path planning method to improve the productivity of AOI (automated optical inspection) machines in PCB (printed circuit board) assembly lines. The path-planning problem is the optimization problem of finding inspection clusters and the visiting sequence of cameras to minimize the overall working time. A unified method is newly proposed to determine the inspection clusters and visiting sequence simultaneously. We apply a hybrid genetic algorithm to solve the highly complicated optimization problem. Comparative simulation results are presented to verify the usefulness of the proposed method.

• Journal of Korean Society of Transportation
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• v.24 no.5 s.91
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• pp.77-88
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• 2006

The purpose of this study is to Propose the time dependent K-least time path algorithm applicable to a real-time based operation strategy in multi-modal transportation network. For this purpose, we developed the extended method based on entire path deletion method which was used in the static K-least time path algorithm. This method was applied to time dependent K-least time path algorithm to find k least time paths in order based on both time dependant mode-link travel time and transfer cost In particular, this algorithm find the optimal solution, easily describing transfer behavior, such as walking and waiting for transfer by applying a link-based time dependent label. Finally, we examined the verification and application of the Proposed algorithm through case study.