• Journal of KIISE:Information Networking
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• v.29 no.4
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• pp.386-396
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• 2002

This paper presents a neural network-based near-optimal routing algorithm. It employs a modified Hopfield Neural Network (MHNN) as a means to solve the shortest path problem. It uses every piece of information that is available at the peripheral neurons in addition to the highly correlated information that is available at the local neuron. Consequently, every neuron converges speedily and optimally to a stable state. The convergence is faster than what is usually found in algorithms that employ conventional Hopfield neural networks. Computer simulations support the indicated claims. The results are relatively independent of network topology for almost all source-destination pairs, which nay be useful for implementing the routing algorithms appropriate to multi -hop packet radio networks with time-varying network topology.

• Journal of Korean Society of Transportation
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• v.34 no.6
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• pp.570-579
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• 2016

This study proposes a concept of Stepwise Transfer Coefficient(STC) which implies greater transfer cost with increasing the number of transfers. Thus, the public transport information system provides the choice sets of travel routes by the consideration of not only transportation time but also the optimum number of transfers. However, path choice problems that involve STC are found to include non additive cost, which requires additional route enumeration works. Discussions on route enumeration in actual transportation networks is very complicated, thereby warranting a theoretical examination of route search considering STC. From these points of view, this study results in a probability based transit trip assignment model including STC. This research also uses incoming link based entire route deletion method. The entire route deletion method proposed herein simplifies construction of an aggregation of possible routes by theoretically supporting the process of enumeration of the different routes from origin to destination. Conclusively, the STC reflected route based logit model is proposed as a public transportation transit trip assignment model.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10b
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• pp.312-314
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• 1998

본 연구에서는 CORBA를 기반으로 Web상에서 관광정보를 제공할 수 있는 관광정보시스템을설계, 개발하였다. CORBA를 기반으로 설계되어 각 지방자치단체나 기관에서 구축, 관리하는 분산 관광정보 데이터베이스에 쉽게 접근할 수 있으며, 상호운용성의 장점을 얻을 수 있다. 본 연구에서 개발된 시스템은 지리정보시스템의 공간분석 기능을 이용하여 사용자가 원하는 특정 출발지로부터 목적지까지 갈 수 있는 최적의 교통 경로를 탐색하고, 특정 관광지를 경유하는 관광코스 분석 기능을 지원하다. 또한 관광지의 지리정보 및 이와 관련된 교통, 숙박 등의 필수 여행정보를 통합, 관리하여 사용자가 통합정보를 파악할 수 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2205-2217
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• 2015

Bio-inspired routing protocol uses a principle of swarm intelligence, which finds the optimal path to the destination in a distributed and autonomous way in dynamic environments, so that it can maximize routing performances, reduce control overhead, and recover a path failure quickly according to the change of network topology. In this paper, we propose a bio-inspired routing protocol for mobile ad hoc networks. The proposed scheme uses a function of overhearing via wireless media in order to obtain the routing information without additional overhead. Through overhearing, the pheromone is diffused around the shortest path between the source and destination. Based on this diffused pheromone, a probabilistic path exploration is executed and the useful alternative routes between the source and destination are collected. Therefore, the proposed routing protocol can ensure the up-to-date routing information while reducing the control overhead. The simulation results show that the proposed scheme outperforms the typical AODV and AntHocNet protocols in terms of routing performances and significantly decreases the routing overhead against the AntHocNet.

• Information Systems Review
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• v.10 no.1
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• pp.115-133
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• 2008

The third-party logistics industry mainly delivers goods from a place to an arrival place on behalf of the freight owner. To handle the work, they need a transportation route including transportation equipment between the starting place and the arrival place, schedule information for departure/arrival and transportation cost. Actually, automatic searching for an optimal transportation route, which considers arrival and departure points for intermodal transportation, is not a simple problem. To search efficiently transportation route, the collection of schedule information for intermodal transportation and transportation route generation have become critical and vital issues for logistics companies. Usually, they manually make a plan for a transportation route by their experience. Because of this, they are limited in their ability if there is too much cargo volume and a great many transactions. Furthermore, their dependence on the conventional way in doing business causes an inefficient selection of transporters or transportation routes. Also, it fails to provide diverse alternatives for transportation routes to the customers, and as a result, increases logistics costs. In an effort to solve these problems, this study aims to develop a route planning system based on agent, which can collect scattered schedule information on the Web. The route planning system also has an algorithm for transportation route generation in intermodal transportation.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4B
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• pp.412-421
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• 2011

An economic ship routing means to sail a ship with a goal of minimizing the fuel consumption by utilizing weather forecast information, and many such systems have been recently developed. Most of them assume that sailing is carried out with a constraint like a fixed output of engine-power or a fixed sailing speed. However, if the output of engine-power is controlled, it is possible to reduce the fuel consumption by sailing a ship under a relatively good weather condition. In this paper, we propose a novel economic ship routing system which can search optimal outputs of the engine-power for each part of a path by employing an evolutionary strategy. In addition, we develope an $A^*$ algorithm to find the shortest path and a method to enhance the degree of curve representation. These make the proposed system applicable to an arbitrary pair of departure and destination points. We compared our proposed system with another existing system not controlling output of the engine-power over 36 scenarios in total, and observed that the former reduced the estimated fuel consumption than the latter by 1.3% on average and the maximum 5.6% with little difference of estimated time of arrival.