• Journal of the Korea Safety Management & Science
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• v.12 no.3
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• pp.315-320
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• 2010

Recently, there are environmental issues for sustainable transportation system to pursue the energy-efficient and environment-friendly public urban transit. These transportation system needs to offer demand-oriented high-quality service being on the same level with cab service for urban space. PRT(Personal Rapid Transit), small track-guided vehicle, is repeatedly mentioned as a possible alternative for the new urban public transportion system, but but there are not many researches on the operational optimal routing for PRT network. In this paper, the concept of PRT and general optimal routing methods are reviewed. And we suggest the optimal routing method for city-wide PRT network with multi-vehicles and stations, junctions and directional arcs. Futher research directions for PRT routing are presented.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.1203-1208
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• 2010

Recently, there are environmental issues for sustainable transportation system to pursue the energy-efficient and environment-friendly public urban transit. These transportation system needs to offer demand-oriented high-quality service being on the same level with cab service for urban space. PRT(Personal Rapid Transit), small track-guided vehicle, is repeatedly mentioned as a possible alternative for the new urban public transportion system, but but there are not many researches on the operational optimal routing for PRT network. In this paper, the concept of PRT and general optimal routing methods are reviewed. And we suggest the optimal routing method for city-wide PRT network with multi-vehicles and stations, junctions and directional arcs. Futher research directions for PRT routing are presented.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.3
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• pp.72-86
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• 2018

Schedule-based public transit routing algorithm computes a single route that calculated minimum travel time using the departure and arrival times for each stop according to vehicle operation plan. However, additional factors such as transfer resistance and alternative route choice are not reflected in the path finding process. Therefore, this paper proposes a improved RAPTOR that reflected transfer resistance and multi-path searching. Transfer resistance is applied at the time of transfer and different values can be set according to type of transit mode. In this study, we analyzed the algorithm's before and after results compared with actual route of passengers. It is confirmed that the proposed algorithm reflects the various route selection criteria of passengers.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.4
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• pp.151-161
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• 2005

For Internet service providers (ISPs), there are three common types of interconnection agreements : private peering, public peering and transit. One of the most important problems for a single ISP is to determine which other ISPs to interconnect with, and under which agreements. The problem can be then to find a set of private peering providers, transit providers and Internet exchanges (IXs) when the following input data are assumed to be given : a set of BGP addresses with traffic demands, and a set of potential service providers (Private peering/transit providers and IXs) with routing information, cost functions and capacities. The objective is to minimize the total interconnection cost. We show that the problem is NP-hard, give a mixed-integer programming model, and propose a heuristic algorithm. Computational experience with a set of test instances shows the remarkable performance of the proposed algorithm of rapidly generating near-optimal solutions.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.82-96
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• 2020

The Demand Responsive Transit (DRT) system is the flexible public transport service that determines the route and schedule of the service vehicles according to users' requests. With increasing importance of public transport systems in urban areas, the development of stable and fast routing algorithms for DRT has become the goal of many researches over the past decades. In this study, a new heuristic method is proposed to generate fast and efficient routes for multiple vehicles using demand clustering and destination demand priority searching method considering the imbalance of users' origin and destination demands. The proposed algorithm is tested in various demand distribution scenarios including random, concentration and directed cases. The result shows that the proposed method reduce the drop of service ratio due to an increase in demand density and save computation time compared to other algorithms. In addition, compared to other clustering-based algorithms, the walking cost of the passengers is significantly reduced, but the detour time and in-vehicle travel time of the passenger is increased due to the detour burden.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.388-393
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• 2005

Private peering, public peering and transit are three common types of interconnection agreements between providers in the Internet. An important decision that an Internet service provider (ISP) has to make is which private peering/transit ISPs and Internet exchanges (IXs) to connect with to transfer traffic at a minimal cost. In this paper, we deal with the problem to find the minimum cost set of private peering/transit ISPs and IXs for a single ISP. There are given a set of destinations with traffic demands, and a set of potential private peering/transit ISPs and IXs with routing information (routes per destination, the average AS-hop count to each destination, etc.), cost functions and capacities. Our study first considers all the three interconnection types commonly used in real world practices. We show that the problem is NP-hard, and propose a heuristic algorithm for it. We then evaluate the quality of the heuristic solutions for a set of test instances via comparison with the optimal ones obtained by solving a mixed integer programming formulation of the problem. Computational results show that the proposed algorithm provides near-optimal solutions in a fast time.