• Asia pacific journal of information systems
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• v.19 no.2
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• pp.117-137
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• 2009

Recently, intelligent traffic information systems have enabled people to forecast traffic conditions before hitting the road. These convenient systems operate on the basis of data reflecting current road and traffic conditions as well as distance-based data between locations. Thanks to the rapid development of ubiquitous computing, tremendous context data have become readily available making vehicle route planning easier than ever. Previous research in relation to optimization of vehicle route planning merely focused on finding the optimal distance between locations. Contexts reflecting the road and traffic conditions were then not seriously treated as a way to resolve the optimal routing problems based on distance-based route planning, because this kind of information does not have much significant impact on traffic routing until a a complex traffic situation arises. Further, it was also not easy to take into full account the traffic contexts for resolving optimal routing problems because predicting the dynamic traffic situations was regarded a daunting task. However, with rapid increase in traffic complexity the importance of developing contexts reflecting data related to moving costs has emerged. Hence, this research proposes a framework designed to resolve an optimal route planning problem by taking full account of additional moving cost such as road traffic cost and weather cost, among others. Recent technological development particularly in the ubiquitous computing environment has facilitated the collection of such data. This framework is based on the contexts of time, traffic, and environment, which addresses the following issues. First, we clarify and classify the diverse contexts that affect a vehicle's velocity and estimates the optimization of moving cost based on dynamic programming that accounts for the context cost according to the variance of contexts. Second, the velocity reduction rate is applied to find the optimal route (shortest path) using the context data on the current traffic condition. The velocity reduction rate infers to the degree of possible velocity including moving vehicles' considerable road and traffic contexts, indicating the statistical or experimental data. Knowledge generated in this papercan be referenced by several organizations which deal with road and traffic data. Third, in experimentation, we evaluate the effectiveness of the proposed context-based optimal route (shortest path) between locations by comparing it to the previously used distance-based shortest path. A vehicles' optimal route might change due to its diverse velocity caused by unexpected but potential dynamic situations depending on the road condition. This study includes such context variables as 'road congestion', 'work', 'accident', and 'weather' which can alter the traffic condition. The contexts can affect moving vehicle's velocity on the road. Since these context variables except for 'weather' are related to road conditions, relevant data were provided by the Korea Expressway Corporation. The 'weather'-related data were attained from the Korea Meteorological Administration. The aware contexts are classified contexts causing reduction of vehicles' velocity which determines the velocity reduction rate. To find the optimal route (shortest path), we introduced the velocity reduction rate in the context for calculating a vehicle's velocity reflecting composite contexts when one event synchronizes with another. We then proposed a context-based optimal route (shortest path) algorithm based on the dynamic programming. The algorithm is composed of three steps. In the first initialization step, departure and destination locations are given, and the path step is initialized as 0. In the second step, moving costs including composite contexts into account between locations on path are estimated using the velocity reduction rate by context as increasing path steps. In the third step, the optimal route (shortest path) is retrieved through back-tracking. In the provided research model, we designed a framework to account for context awareness, moving cost estimation (taking both composite and single contexts into account), and optimal route (shortest path) algorithm (based on dynamic programming). Through illustrative experimentation using the Wilcoxon signed rank test, we proved that context-based route planning is much more effective than distance-based route planning., In addition, we found that the optimal solution (shortest paths) through the distance-based route planning might not be optimized in real situation because road condition is very dynamic and unpredictable while affecting most vehicles' moving costs. For further study, while more information is needed for a more accurate estimation of moving vehicles' costs, this study still stands viable in the applications to reduce moving costs by effective route planning. For instance, it could be applied to deliverers' decision making to enhance their decision satisfaction when they meet unpredictable dynamic situations in moving vehicles on the road. Overall, we conclude that taking into account the contexts as a part of costs is a meaningful and sensible approach to in resolving the optimal route problem.

• Journal of the Korea Society of Computer and Information
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• v.4 no.1
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• pp.38-46
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• 1999

One of the tasks of maritime navigation is to decide upon the optimal navigation route that minimizes a vessals travel time and fuel consumption. Recently. ECDIS(Electronic Chart Display Information System) is used to decide the optimal navigation route and have expert knowledge of maritime navigation. In this paper, the system use $A^*$algorithm for optimal navigation route on ECDIS. But some problems is discovered in this situation. it requires many memory device and searching time. So this paper has tried to develope a advanced algorithm system that decides the optimal navigation route.

• 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.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.513-516
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• 2013

Earthmoving equipment's haul-route has a great influence on the productivity of the earth work operation. Haul-route grade is a critical factor in selecting the haul-route. The route that has low grade resistance contributes to increase machine travel speed and production. This study presents a mathematical model called "Hauling-Unit Optimal Routes Selecting system" (HUORS). The system identifies optimal path that maximize the earth-work productivity. It consists of 3 modules, i.e., (1) Module 1 which inputs site characteristic data and computes site location and elevation using GIS(Geographical Information System); (2) Module 2 which calculates haul time; (3) Module 3 which displays an optimum haul-route by considering the haul-route's gradient resistances (i.e., from the departure to the destination) and hauling time. This paper presents the system prototype in detail. A case study is presented to demonstrate the system and verifies the validity of the model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.50
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• pp.333-340
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• 1999

An ideal traffic control system should consider simultaneously both route guidance of vehicles and signal policies at intersection of a traffic network. It is known that an iterative procedure gives an optimal route to each vehicle in the network. This paper presents an iterative procedure to find an optimal signal plan for the network. We define the optimal solution as a signal equilibrium. From the definition of signal equilibrium, we prove that the fixed point solution of the iterative procedure is a signal equilibrium, when optimal signal algorithms are implemented at each intersection of the network. A combined model of route guidance and signal planning is also suggested by relating the route guidance procedure and the signal planning procedure into a single loop iterative procedure.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.4 no.3 s.8
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• pp.9-22
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• 2005

Route travel cost in transportation networks consists of actual route travel cost and route perception cost. Since the route perception cost is differently perceived according to each origin and each destination, route search has limitation to reflect the note perception cost due to route enumeration problem. Thus, currently employed advanced traveller information systems (ATIS) have considered only actual route travel cost for providing route information. This study proposes an optimal and a K-route searching algorithm which are able to reflect the route perception cost but encompass route enumeration problem. For this purpose, this research defines the minimum nit of route as a link by adopting the link label technique in route searching, therefore the comparison of two adjacent links which can be finally expanded the comparison of two routes. In order to reflect the characteristics of route perception in real situation, an optimal shortest cost path algorithm that both the forward search from the origin and the backward search from the destination can be simultaneously processed is proposed. The proposed algorithm is applied for finding K number of shortest routes with an entire-path-deletion-type of K shortest route algorithm.

• 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 Operations Research and Management Science Society
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• v.6 no.1
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• pp.5-13
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• 1981

This paper considers a facility moving along a route of straight line to serve several facilities in xy plane. A route is obtained which minimizes the objective function expressed in terms of average rectilinear distance between the service facility and facilities to he served. The forms of the objective functions can be classified into several cases according to the initial and end points of the routes. In some cases, as in the problem of optimal location of new facility, the cordinates of the optimal routes are median of the cordinates of facilities to be served. In others, the optimal routes are obtained after examining the values of objective functions on the boundaries of slopes and intercepts. An overall optimal route is obtained by comparing these routes. The entire procedure has been programmed in BASIC language, and several case examples are given.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.89.6-89
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• 2001

In Vehicle Information and Communication System (VICS), which is an active field of Intelligent Transport System (ITS), information of traffic congestion is sent to each vehicle at real time. However, a centralized navigation system is not realistic to guide millions of vehicles in a megalopolis. Autonomous distributed systems should be more flexible and scalable, and also have a chance to focus on each vehicle´s demand. This paper proposes a sub-optimal route planning mechanism of vehicles in urban areas using the non-network type immune system. Simulation is carried out using a cellular automaton model. This system announces a sub-optimal route to drivers in real time using VICS.

• 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.