• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.08a
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• pp.167-176
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• 2004

The authors have newly developed the “Port Traffic Management System (PTMS)”. The PTMS provides each ship with the detailed planned routes of all the ships entering/leaving the port. This system also has a function to predict the encounter situations between own ship and other ships in the future. Based on information of the present positions, speeds and planned routes of the own ship and other ships, it is possible to predict when and where the own ship will have dangerous encounters with other ships in the future. The software of PTMS was developed from 2001. Then onboard experiments using small training ships equipped with actual AIS were performed in June 2003. From the results of these onboard experiments, the usefulness of PTMS was clarified. In addition to these onboard experiments, the effectiveness of PTMS was confirmed by comprehensive simulator experiments. In the simulator experiments, captains/pilot maneuvered a training ship/container ship in congested waters using PTMS. [t was assumed that all ships have PTMS and send their planned routes. After the simulator experiments, captains/pilot suggested that it is very beneficial if the optimal route of own ship can be automatically calculated. In response to this suggestion, software to calculate the optimal route of own ship using Dynamic Programming was developed. This software calculates the minimum time route from the present position to the destination keeping the danger of collision against other ships under predetermined level. From the result of calculations for multi-encounter situations, it was confirmed that the developed software can provide safe and time-saving route.

• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.19-27
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• 2007

We have implemented a WWW homepage which finds an optimal route for users. There already exist many web sites which provide the optimal route when a start and a destination cities are given. However, none of them can find the optimal route when a number of cities to be visited. The problem of finding the optimal route starting at a given start city and visiting through all the given intermediate cities and finally returning to the start city is called Travelling Sales Person(TSP) problem. TSP is a well known exponential time complexity problem. We have implemented an artificial intelligent search algorithm for TSP on our homepage. The main feature of our algorithm is that the destination may not be the same as the start city whereas all of the existing heuristic algorithms for TSP assume that the start and the destination cities are the same. The web page asks a user to select all the cities he or she wants to visit(including start and destination city), then it finds a sequence of the cities such that the user would travel minimum distance if he or she visits the cities in the order of the sequence. This paper presents algorithms used in the homepage.

• Journal of Communications and Networks
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• v.14 no.1
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• pp.91-103
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• 2012

Network mobility (NEMO) based on mobile IP version 6 has been proposed for networks that move as a whole. Route optimization is one of the most important topics in the field of NEMO. The current NEMO basic support protocol defines only the basic working mode for NEMO, and the route optimization problem is not mentioned. Some optimization schemes have been proposed in recent years, but they have limitations. A new NEMO route optimization scheme-involving a combination of the optimized route cache protocol (ORC) and reverse routing header (RRH) and the use of a quota mechanism for optimized sessions (OwR)-is proposed. This scheme focuses on balanced performance in different aspects. It combines the ORC and RRH schemes, and some improvements are made in the session selection mechanism to avoid blindness during route optimization. Simulation results for OwR show great similarity with those for ORC and RRH. Generally speaking, the OwR's performance is at least as good as that of the RRH, and besides, the OwR scheme is capable of setting up optimal routing for a certain number of sessions, so the performance can be improved and the cost of optimal routing in nested NEMO can be decreased.

• Korean Journal of Computational Design and Engineering
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• v.17 no.2
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• pp.71-78
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• 2012

Recently, the ratio of fuel cost to the operational cost of a ship is increasing according to the increase of the international oil price. Thus, many studies are being made to reduce the cost; for example, a method for acquiring the sea state information, a method for estimating fuel consumption, a method for determining the ship's optimal route, and so on. However, these studies were not incorporated together and being independently made in different fields. In this study, by improving and incorporating such studies, a method for determining a ship economic route based on the acquisition of the sea state and estimation of fuel consumption was proposed. To evaluate the applicability of the proposed method, it was applied to an optimal routing problem of the ocean area including many islands. The result shows that the proposed method can yield the economic route minimizing fuel consumption.

• Proceedings of the KOR-KST Conference
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• 2000.02a
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• pp.25-47
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• 2000

In route guidance systems fastest-path routing has typically been adopted because of its simplicity. However, empirical studies on route choice behavior have shown that drivers use numerous criteria in choosing a route. The objective of this study is to develop computationally efficient algorithms for identifying a manageable subset of the nondominated (i.e. Pareto optimal) paths for real-time vehicle routing which reflect the drivers' preferences and route choice behaviors. We propose two pruning algorithms that reduce the search area based on a context-dependent linear utility function and thus reduce the computation time. The basic notion of the proposed approach is that ⅰ) enumerating all nondominated paths is computationally too expensive, ⅱ) obtaining a stable mathematical representation of the drivers' utility function is theoretically difficult and impractical, and ⅲ) obtaining optimal path given a nonlinear utility function is a NP-hard problem. Consequently, a heuristic two-stage strategy which identifies multiple routes and then select the near-optimal path may be effective and practical. As the first stage, we utilize the relaxation based pruning technique based on an entropy model to recognize and discard most of the nondominated paths that do not reflect the drivers' preference and/or the context-dependency of the preference. In addition, to make sure that paths identified are dissimilar in terms of links used, the number of shared links between routes is limited. We test the proposed algorithms in a large real-life traffic network and show that the algorithms reduce CPU time significantly compared with conventional multi-criteria shortest path algorithms while the attributes of the routes identified reflect drivers' preferences and generic route choice behaviors well.

• Journal of Convergence for Information Technology
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• v.9 no.10
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• pp.56-63
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• 2019

The purpose of this paper is to derive an optimal route for foreign tourists in Korea. To that end, the data gained from domestic tourist portal sites was analyzed with a big data analytics tool R. The destinations most visited by inbound foreign tourists, the shortest route and the most economical route were derived from the analysis results. The findings suggest original Korean culture is the factor for successful tourist destinations and relevant products, and will serve as some reference data conducive to planning the tourist products in practice.

• Korean Journal of Hazardous Materials
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• v.3 no.1
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• pp.28-36
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• 2015

In early 2011, the Fukushima nuclear power plant had greater damage due to earthquake in Japan, and the awareness of safety has increased. In particular, special response systems should be required to handle disaster situations in plant sites which are likely to occur for large disasters. In this study, a program is designed to set up optimum escape routes, by a smart phone application, when a disaster situation occurs. This program could get information of the cumulative damage from sensors and display the escape route of the smallest damage in real-time on the screen. Utilizing our application in real-time evacuation has advantage in reducing cumulative damage. The optimal evacuation route, focusing on horizontal path, is calculated based on getting the data of fire, detected radioactivity and hazardous gas. Thus, using our application provides information of optimal evacuation to people who even can not hear sensor alarms or do not know geography, without requiring additional costs except fixed sensors or server network deployment cost. As a result, being informed of real-time escape route, the user could behave rapidly with suitable response to individual situation resulting in improved evacuation than simply reacting to existing warning alarms.

• Journal of Digital Contents Society
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• v.6 no.1
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• pp.55-62
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• 2005

In this paper, we propose the new technique to compute the optimal route by considering the direction of distribution vehicles and the location for delivery, developing the algorithm of the shortest route to approach the location as applying the gemetic algorithm. This approach makes it possible for us to find the best route even under itineraries which include many destinations. Lively studies are currently in progress on the development of vehicle navigation software, combining PDA GPS, and electronic maps. Many web-sites are providing a varier of services which use electronic maps. Popular among these services is one that computes the optimal route between two positions that a user inputs. This service of computing the optimal route plays an important role in distribution industries such as home-delivery. For the distribution system. the construction of a vehicle regulation system enables us to calculate and manipulate the optimal route for distribution vehicles, to enhance the efficiency in making use of vehicles and labor, and to reduce costs.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.4 s.34
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• pp.39-46
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• 2005

This paper use virtual running after possible traffic capacity application for optimal route location. General road is designed the design after we examine an alternate adequacy investigation and an execution design sufficiently. Various road user's requirement must be reflected from the beginning. But it is difficult to contain the various suitable design criteria because we consider the existing 2-dimension element. First of all, this study chose optimal route, used traffic assignment and 3D simulation. Then selected optimal route through the consistent road construction by analyzing road driving simulation of 3-dimension data and the urban landscape. possible traffic capacity and virtual running will be able to do the urban landscape analysis harmonizing with the environment; equally, it could be objectively solve the problem of a civil appeal.

• 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.