• International conference on construction engineering and project management
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• 2024.07a
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• pp.242-246
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• 2024

Automated route planning is an important tool in the field of built environment. For example, a high-quality route planning method can improve the logistics planning of projects, thereby enhancing the performance of projects and the effectiveness of management. However, the traditional automated route planning is performed based on the predicted mean value travel time of candidate routes. Such a point estimate neglects the purpose of the trip and can further lead to a suboptimal decision. Motivated by this challenge, this study proposes an innovative framework for trip purpose based route planning. The proposed artificial intelligence and stochastic optimization framework recommends the most appropriate travel route for decision makers by fully considering their trip requirements beyond just the shortest mean value travel time. In addition to its theoretical contributions, our proposed route planning method will also contribute to the current logistics planning practice. Future research may be devoted to the real-life implementation of the proposed methodology in a broader context to provide empirical insights for practitioners in various industries.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.11
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• pp.634-639
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• 2002

A Shortest Path Algorithm is the method to find the most efficient route among many routes from a start node to an end node. It is based on Labeling methods. In Labeling methods, there are Label-Setting method and Label-Correcting method. Label-Setting method is known as the fastest one among One-to-One shortest path algorithms. But Benjamin[1,2] shows Label-Correcting method is faster than Label-Setting method by the experiments using large road data. Since Graph Growth algorithm which is based on Label-Correcting method is made to find One-to-All shortest path, it is not suitable to find One-to-One shortest path. In this paper, we propose a new One-to-One shortest path algorithm. We show that our algorithm is faster than Graph Growth algorithm by extensive experiments.

• Management Science and Financial Engineering
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• v.12 no.2
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• pp.87-110
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• 2006

In a hierarchical road network, all roads can be classified according to their attributes such as speed limit, number of lanes, etc. By splitting the whole road network into the subnetworks of the highlevel and low-level roads, we can reduce the size of the network to be calculated at once, and find a path in the way that drivers usually adopt when searching out a travel route. To exploit the hierarchical property of road networks, we define a convenient path and propose an algorithm for finding convenient paths. We introduce a parameter indicating the driver's tolerance to the difference between the length of a convenient path and that of a shortest convenient path. From this parameter, we can determine how far we have to search for the entering and exiting gateway. We also propose some techniques for reducing the number of pairs of entries and exits to be searched in a road network. A result of the computational experiment on a real road network is given to show the efficiency of the proposed algorithm.

• Journal of Korean Society of Transportation
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• v.23 no.6 s.84
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• pp.91-102
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• 2005

When it comes to the process of information storage, people are likely to organize individual information into the forms of groups rather than independent attributes, and put them together in their brains. Likewise, in case of finding the shortest path, this study suggests that a Hierarchical Road Network(HRN) model should be selected to browse the most desirable route, since the HRN model takes the process mentioned above into account. Moreover, most of drivers make a decision to select a route from origin to destination by road hierarchy. It says that the drivers feel difference between the link travel tine which was measured by driving and the theoretical link travel time. There is a different solution which has predicted the link travel time to solve this problem. By using this solution, the link travel time is predicted based on link conditions from time to time. The predicated link travel time is used to search the shortest path. Stochastic Process model uses the historical patterns of travel time conditions on links. The HRN model has compared favorably with the conventional shortest path finding model in tern of calculated speeds. Even more, the result of the shortest path using the HRN model has more similar to the survey results which was conducted to the taxi drivers. Taxi drivers have a strong knowledge of road conditions on the road networks and they are more likely to select a shortest path according to the real common sense.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.4
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• pp.315-320
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• 2015

Proposal algorithm in this paper introduced cells, units of router group, for distributed processing of previous genetic algorithm. This paper presented ways to reduce search delay time of overall network through cell-based genetic algorithm. As a result of performance analysis comparing with existing genetic algorithm through experiments, the proposal algorithm was verified superior in terms of costs and delay time. Furthermore, time for routing an alternative path was reduced in proposal algorithm, in case that a network was damaged in existing optimal path algorithm, Dijkstra algorithm, and the proposal algorithm was designed to route an alternative path faster than Dijkstra algorithm, as it has a 2nd shortest path in cells of the damaged network. The study showed that the proposal algorithm can support routing of alternative path, if Dijkstra algorithm is damaged in a network.

• Journal of The Korean Association of Information Education
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• v.2 no.2
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• pp.252-259
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• 1998

Vehicle navigation systems employ a certain route planning algorithm that provides the shortest path between the starting point and the destination point. The performance of a given route planning algorithm is measured through the degree of optimal route selection and the time cost to complete searching an optimal path. In this paper, various route planning algorithms are evaluated through computer simulation based on a real digital map database. Among those algorithms evaluated in this paper, the Modified Bi-directional A${\ast}$ algorithm is found to be the best algorithm for use in vehicle navigation systems.

• Journal of information and communication convergence engineering
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• v.6 no.4
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• pp.396-404
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• 2008

Service discovery is the technology of finding needed services in networks, and a key point in pervasive computing environments. This paper presents a novel service discovery protocol: ASESDP(AIP and SRR Enhanced Service Discovery Protocol). In ASESDP, tow schemes are proposed to enhance its performance: AIP(Advertisement Information Piggybacked) and SRR(Shortest Reply Route). In AIP, parts of advertisement information are piggybacked in the service reply packet, which makes the advertisement information propagating along the reply path, and spreads its transmission area. In SRR, in order to reduce the service response time, the shortest reply route is chosen to forward the service reply packet to the source node sending the service request. With the theoretical analysis and Glomosim simulation results, it is verified that ASESDP can reduce the number of service request packets, save the response time, and improve the efficiency of service discovery.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.2
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• pp.78-97
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• 2010

Route discovery in wireless mobile networks requires a considerable amount of resources due to the mobility of the hosts. Therefore, it would be wise to utilize the effort already invested in existing paths. This paper proposes an efficient way to reuse, whenever possible, existing paths when a new path is being established. In our proposed algorithm, called Route Reutilization Routing (RRR), the reusability is accomplished by the notion of the dynamic proactive zones (DPZ), through which nearby existing path information is disseminated. By utilizing the information stored in DPZs, RRR can achieve considerable savings over other on-demand routing algorithms that use flooding. The unique feature of the proposed algorithm is that DPZs are created and destroyed dynamically around the existing paths, whereas proactive zones are formed around the nodes throughout the network in other route finding algorithms. Even though using DPZs may not result in the shortest path between source and destination, simulation results show the considerable reduction in traffic needed to find a path and therefore increases the available bandwidth for data transmission.

• Journal of the Society of Naval Architects of Korea
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• v.44 no.3 s.153
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• pp.340-347
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• 2007

Main purpose of the study is to develop a transit model for icebreaking cargo vessels in the Northern Sea Route and to select optimum sea routes with the shortest navigation time and the lowest operation cost. This numerical model executed with basic information such as ship capabilities, transit directions and months of transit, can calculate total transit distance and elapsed time, mean speed, operation cost for each vessel. In the transit model. environment information such as the site-specific ice conditions, wave and wind states are utilized for four different months (April, June, August, and October) along the Northern Sea Route. The model also defines a necessary period of an icebreaker escort. Then the optimum sea routes are selected and visually displayed on the digital map using a commercial software ArcGIS. Usefulness of the selected sea routes is discussed.