• Proceedings of the Korean Institute of Building Construction Conference
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• 2014.05a
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• pp.4-5
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• 2014

Planning earthmoving haul-route must be preceded for appropriate equipment fleet assignment. However, traditional haul-route planning methods have limitations relative to practical usage because multiple variables (e.g., grade/rolling resistance, length, equipment's weight etc.) should be considered at a time. Genetic algorithm(GA) was introduced to improve these traditional methods. However, GA based haul-route planning method still remains in inefficiency relative to computation performance. This study presents a new haul-route searching method that computes an optimal haul-route using GA. The system prototype is developed by using MATLAB(ver. 2008b). The system identifies an optimal haul-route by considering equipment type, soil type, and soil condition.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.4
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• pp.469-478
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• 2012

This study aims to discover the optimal pipe layout for a ship, which generally needs a lot of time, efforts and experiences. Genetic algorithm was utilized to search for the optimum. Here the optimum stands for the minimum pipe length between two given points. Genetic algorithm is applied to planar pipe layout problems to confirm plausible and efficiency. Sub-programs are written to find optimal layout for the problems. Obstacles are laid in between the starting point and the terminal point. Pipe is supposed to bypass those obstacles. Optimal layout between the specified two points can be found using the genetic algorithm. Each route was searched for three case models in two-dimensional plane. In consequence of this, it discovered the optimum route with the minimized distance in three case models. Through this study, it is possible to apply optimization of ship pipe route to an actual ship using genetic algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.407-411
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• 1992

A method for optimal route planning is presented with the assumption that the overall defended area is known in terms of threat potential function. This approach employes tangent plane to reduce the dimension of the state space for optimal programming problems with a state equality constraint. One-dimensional search algorithm is used to select the optimal route among the extermal fields which are obtained by integrating three differential equations from the initial values. In addition to being useful for the route planning through threat potential area, the trajectory planning will be suitable for general two-dimensional searching problems.

• Journal of the Society of Naval Architects of Korea
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• v.56 no.6
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• pp.480-487
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• 2019

Ship route planning is to find a route to minimize voyage time and/or fuel consumption in a given sea state. Unlike previous studies, this study proposes an optimization method for the route planning to avoid the grounding risk near the coast. The route waypoints were searched using A^* algorithm, and the route simplification was performed to remove redundant waypoints using Douglas-Peucker algorithm. The optimization was performed to minimize fuel consumption by setting the optimization design parameters to the engine rpm. The sea state factors such as wind, wave, and current are also considered for route planning. We propose the constraint to avoid ground risk by using under keel clearance obtained from electoronic navigational chart. The proposed method was applied to find the optimal route between Mokpo and Jeju. The result showed that the proposed method suggests the optimal route that minimizes fuel consumption.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.5
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• pp.425-433
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• 2012

Dijkstra's algorithm is one of well-known methods to find shortest paths over a network. However, more research on $A^*$ algorithm is necessary to discover the shortest route to a goal point with the heuristic information rather than Dijkstra's algorithm which aims to find a path considering only the shortest distance to any point for an optimal path search. Therefore, in this paper, we compared Dijkstra's algorithm and $A^*$ algorithm for bicycle route selection. For this purpose, the horizontal distance according to slope angle and average speed were calculated based on factors which influence bicycle route selection. And bicycle routes were selected considering the shortest distance or time-dependent shortest path using Dijkstra's or $A^*$ algorithm. The result indicated that the $A^*$ algorithm performs faster than Dijkstra's algorithm on processing time in large study areas. For the future, optimal path selection algorithm can be used for bicycle route plan or a real-time mobile services.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.6
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• pp.1091-1098
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• 2010

Victory and defeat of the war depends on follow-on logistics support. The spending time of follow-on logistics support at combat area is greatly influenced by the degree of combat intensity. The main purpose of this study is to compose a optimal supply route for operational sustainability of combat unit at combat area using transport vehicles. This study suggests a composition of optimal supply route for follow-on logistics support which considers the degree of combat intensity. A mathematical programming model and a genetic algorithm suggest to minimize the total spending time of follow-on logistics support. The suggested mathematical programming model is verified by using CPLEX 11.1. This study computes supply route, total spending time, total travel distance, and the number of transport vehicle.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.265-275
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• 2023

The purpose of this paper is to devise an optimal route allocation algorithm for automated vehicle(AV) in monitoring quality of road infrastructure to support the road safety. The tasks of an AV in this paper include visiting node-links at least once during its operation and checking status of road infrastructure, and coming back to its depot.. In selecting optimal route, its priority goal is visiting the node-links with higher risks while reducing costs caused by operation. To deal with the problem, authors devised reward maximizing algorithm for AVs. To check its validity, the authors developed simple toy network that mimic node-link networks and assigned costs and rewards for each node-link. With the toy network, the reward maximizing algorithm worked well as it visited the node-link with higher risks earlier then chinese postman route algorithm (Eiselt, Gendreau, Laporte, 1995). For further research, the reward maximizing algorithm should be tested its validity in a more complex network that mimic the real-life.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.137-143
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• 2017

In this paper, we propose optimal route searching algorithm using ANN(Artificial Neural Network) and implement route searching system. Our proposed scheme shows that the route using artificial neural network is almost same as the route using Dijkstra's algorithm but the time in our propose algorithm is shorter than that of existing Dijkstra's algorithm. Proposed route searching method using artificial neural network has better performance than exiting route searching method because it use several weight value in making different routes. Through simulation, we show that our proposed routing system improves the performance and reduces time to make route irrespective of the number of hidden layers.

• The Journal of Information Systems
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• v.9 no.1
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• pp.235-255
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• 2000

Facing in very rapidly changing environments via information technologies, we need to study and develop new information technologies in postal delivery service in korea. We study to find the near optimal route for the better postal service between the collection centers. Optimal routing decision for the postal delivery is NP-Hard. The main purpose of this paper is to develop the near optimal simulation technique for the postal routing decision We consider the distance between collection centers, and the quantity of post articles in the collection center to obtain the near optimal route. We use the heuristic algorithm to obtain the near optimal solution for the transportation route of postal articles. Also, we try to show the transportation route by using the map after deciding the near optimal route.

• Proceedings of the Korea Association of Information Systems Conference
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• 2000.11a
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• pp.45-63
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• 2000

Facing in very repidly changing environments via information technologies, we need to study and develop new information technologies in postal delivery service in Korea. We study to find the near optimal route for the better postal service between the collection centers. Optimal routing decision for the postal delivery is NP-Hard. The main purpose of this paper is to develop the near optimal simulation technique for the postal routing decision. We consider the distance between collection centers, and the quantity of post articles in the collection center to obtain the near optimal route. We use the heuristic algorithm to obtain the near optimal solution for the transportation route of postal articles. Also, we try to show the transportation route by using the map after deciding the near optimal route.