• Journal of Korean Institute of Industrial Engineers
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• v.28 no.3
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• pp.256-263
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• 2002

This paper addresses a planning problem in a pickup-delivery transportation' system under dynamic vehicle dispatching. We present a procedure to determine a fleet size in which stochastic characteristics of vehicle travels are considered. Statistical approach and queueing theory are applied to estimate vehicle travel time and vehicle waiting time, based on which an appropriate fleet size is determined. Simulation experiments are performed to verify the proposed procedure.

• Management Science and Financial Engineering
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• v.18 no.1
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• pp.27-37
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• 2012

This paper is motivated by a military cargo-plane routing problem which is a pickup-and-delivery problem in which load splits and node revisits are allowed (PDPLS). Although this recent evolution of a VRP-model enhances the efficiency of routing, a solution method is more of a challenge since the node revisits entail closed walks in modeling vehicle routes. For such a case, even a compact IP-formulation is not available and an effective method had been lacking until Nowak et al. (2008b) proposed a heuristic based on a tabu search. Their method provides very reasonable solu-tions as demonstrated by the experiments not only in their paper (Nowak et al., 2008b) but also in ours. However, the computation time seems intensive especially for the class of problems with dynamic transportation requests, including the military cargo-plane routing problem. This paper proposes a more scalable algorithm hybridizing a tabu search for pricing subproblem paused as a single-vehicle routing problem, with a column generation approach based on Dantzig-Wolfe decomposition. As tested on a wide variety of instances, our algorithm produces, in average, a solution of an equiva-lent quality in 10~20% of the computation time of the previous method.

• IE interfaces
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• v.12 no.4
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• pp.557-566
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• 1999

This paper considers a door-to-door service system in which pickups or deliveries are performed by a trip of a single vehicle. Each customer request specifies the quantity of the load transported, the location, and the time window within which it is to be picked up or delivered. Since the system is demand responsive, i.e., new or emergent requests become available in real-time, the current vehicle route has to be reconstructed to include these requests. In this case, only continuous vehicle tracking enables control over the requests and ensures that the requests are satisfied on time. This paper suggests a pilot pickup/delivery management system integrating a geographic information system(GIS) and a global position system(GPS) to efficiently deal with such a dynamic environment. The GIS offers a way of displaying the vehicle route on digital maps for the region under concerned. Also displayed is the current location of the vehicle obtained from the GPS. A heuristic algorithm is used to dynamically determine the vehicle route. A practical example is provided to show the feasibility of the system.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.139-142
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• 2001

This study suggests an approach for determining fleet size for container road transportation with dynamic demand in Korea. With the forecasted monthly container transportation data a year, a heuristic algorithm is developed to determine the number of company-owned trucks, mandated trucks, and rented trucks in order to minimize the expected annual operating cost, which is based on the solution technologies used in the aggregate production planning and the pickup-and-delivery problem. Finally the algorithm is tested for the problem how the trucking company determines the fleet size for transporting containers.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.97-109
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• 2014

Personal rapid transit (PRT) is a new transportation system, which is energy efficient and brings high quality of customer service. Customers arrive dynamically at stations and request transportation service. In this paper, we propose a new online PRT dispatching algorithm for pickup and delivery of customers. We adopt the nearest neighbor dispatching rule, which is known as performing well in general. We extend the rule with bipartite matching in order to deal with multiple vehicles and customers at the same time. We suggest a systematic way for selecting vehicles that will be considered to be dispatched, since the scope with which vehicles are selected may affect the system performance. We regard the empty travel distance of vehicles and the customer waiting time as the performance measures. By using simulation experiments, it has been examined that the scope of dispatching affects the system performance. The proposed algorithm has been validated by comparing with other dispatching rules for transportation services. We have shown that our algorithm is more suitable for PRT operating environment than other dispatching rules.

• IE interfaces
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• v.17 no.1
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• pp.71-77
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• 2004

At the present time, container transportation plays a key role in the international logistics and the efforts to increase the productivity of container logistics become essential for Korean trucking companies to survive in the domestic as well as global competition. This study suggests an approach for determining fleet size for container road transportation with dynamic demand. Usually the vehicles operated by the transportation trucking companies in Korea can be classified into three types depending on the ways how their expenses occur; company-owned truck, mandated truck which is owned by outsider who entrust the company with its operation, and rented vehicle (outsourcing). Annually the trucking companies should decide how many company-owned and mandated trucks will be operated considering vehicle types and the transportation demands. With the forecasted monthly data for the volume of containers to be transported a year, a heuristic algorithm using tabu search is developed to determine the number of company-owned trucks, mandated trucks, and rented trucks in order to minimize the expected annual operating cost. The idea of the algorithm is based on both the aggregate production planning (APP) and the pickup-and-delivery problem (PDP). Finally the algorithm is tested for the problem how the trucking company determines the fleet size for transporting containers.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.11
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• pp.1578-1586
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• 2015

Personal rapid transit (PRT) is getting attention as a new form of transportation. It is energy efficient and provides the high level of passenger service. In this study, the dynamic PRT dispatching and routing problem is dealt with. Passengers request transportation service on a complex network, and an operating system monitors passenger arrivals and coordinates vehicles in real time. A new online dispatching and routing algorithm is proposed, which minimizes the total travel distance of vehicles and the waiting time of passengers. The algorithm dispatches vehicles by considering multiple vehicles' state and multiple passengers at the same time. In particular, finding the shortest-time path is attempted by taking into account the future congestion on lanes. Discrete-event simulation is employed to validate the performance of the proposed algorithm. The results show the algorithm in this study outperforms others.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.171-178
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• 2002

At the present time, container transportation plays a key role in the international logistics and the efforts to increase the productivity of container logistics become essential for Korean trucking companies to survive in the domestic as well as global competition. This study suggests an approach for determining fleet size for container road transportation with dynamic demand. Usually the vehicles operated by the transportation trucking companies in Korea can be classified into three types depending on the ways how their expenses occur; company-owned truck, mandated truck which is owned by outsider who entrust the company with its operation, and rented vehicle (outsourcing). Armually the trucking companies should decide how many company-owned and mandated trucks will be operated considering vehicle types and the transportation demands. With the forecasted monthly data for the volume of containers to be transported a year, a heuristic algorithm using tabu search is developed to determine the number of company-owned trucks, mandated trucks, and rented trucks in order to minimize the expected annual operating cost The idea of the algorithm is based on both the aggregate production planning (APP) and the pickup-and-delivery problem (PDP). Finally the algorithm is tested for the problem how the trucking company determines the fleet size for transporting containers.

• Journal of Korean Society of Transportation
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• v.22 no.2 s.73
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• pp.145-154
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• 2004

The growing demand for customer-responsive, made-to-order manufacturing is stimulating the need for improved dynamic decision-making processes in commercial fleet operations. Moreover, the rapid growth of electronic commerce through the internet is also requiring advanced and precise real-time operation of vehicle fleets. Accompanying these demand side developments/pressures, the growing availability of technologies such as AVL(Automatic Vehicle Location) systems and continuous two-way communication devices is driving developments on the supply side. These technologies enable the dispatcher to identify the current location of trucks and to communicate with drivers in real time affording the carrier fleet dispatcher the opportunity to dynamically respond to changes in demand, driver and vehicle availability, as well as traffic network conditions. This research investigates key aspects of real time dynamic routing and scheduling problems in fleet operation particularly in a truckload pickup-and-delivery problem under various settings, in which information of stochastic demands is revealed on a continuous basis, i.e., as the scheduled routes are executed. The most promising solution strategies for dealing with this real-time problem are analyzed and integrated. Furthermore, this research develops. analyzes, and implements hybrid algorithms for solving them, which combine fast local heuristic approach with an optimization-based approach. In addition, various partitioning algorithms being able to deal with large fleet of vehicles are developed based on 'divided & conquer' technique. Simulation experiments are developed and conducted to evaluate the performance of these algorithms.