• Journal of Digital Convergence
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• v.15 no.10
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• pp.31-43
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• 2017

This study was aimed at analyzing the operational efficiency of DPAs(the delivery and pickup agents), which serve as sub-terminals in parcel delivery services, using CCR/BCC models in DEA. The input variables included the number of employees, and the amount of equipment and the operating expenses. The output variable was revenue value. The efficiency for the period from 2014 to 2016 was analyzed. The results revealed that the operational efficiency improved in 2016, compared with 2014, in both CCR and BCC models. According to the benchmarking analysis, DMU 1 and DMU 7 showed higher efficiency in 2016. The inefficiency analysis based on the BCC model showed increased efficiency of all factors in 2016 when compared with 2014. The Malmquist productivity index (MPI) dropped slightly as a result of technical changes and indicated a declining technical efficiency in all DMUs. This study suggests the need for government-led systematic improvement and support for DPAs by providing current insight into the parcel delivery industry and analyzing DPAs' operational efficiency in Korea for the first time. This research performed efficiency analysis of DPAs located in new town of paju and gimpo cities. In future research, comparative study on efficiency analysis including new town, old town area, and other cities are needed.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.2
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• pp.141-155
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• 2006

In this paper, we address an extended hub-and-spoke transportation network design problem (EHSNP). In the existing hub location problems, the location and number of spokes, and shipments on spokes are given as input data. These may, however, be viewed as the variables according to the areas which they cover. Also, the vehicle routing in each spoke needs to be considered to estimate the network cost more correctly. The EHSNP is a problem of finding the location of hubs and spokes, and pickup/delivery routes from each spoke, while minimizing the total related transportation cost in the network. The EHSNP is an integrated problem that consists of several interrelated sub-problems. To solve EHSNP, we present an approach based on a symbiotic evolutionary algorithm (symbiotic EA), which are known as an efficient tool to solve complex integrated optimization problems. First, we propose a framework of symbiotic EA for EHSNP and its genetic elements suitable for each sub-problem. To analyze the proposed algorithm, the extensive experiments are performed with various test-bed problems. The results show that the proposed algorithm is promising in solving the EHSNP.

• 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.

• 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.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1248-1251
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• 2002

Logistics optimization problems related with vehicle routing such as warehouse locating, track scheduling, customer order delivery, wastage pickup etc. are very interesting and important issues to date. Many Vehicle Routing and Scheduling Systems (VRSS) have been developed/proposed to optimize the logistics problems. But majority of them are dedicated to a particular problem and are unable to handle the real world spatial data directly. The system developed for one problem may not be suitable for others due to inter-problem constraint variations. The constraints may include geographical, environmental and road traffic nature of the working region along with other constraints related with the problem. So the developer always needs to modify the original routing algorithm in order to fulfill the purpose. In our study, we propose a general-purpose platform by combining GIS road map and Database Management System (DBMS), so that VRSS can interact with real world spatial data directly to solve different kinds of vehicle routing problems. Using the features of our developed system, the developer can frequently modify the existing algorithm or create a new one to serve the purpose.

• 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.