• 대한산업공학회지
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• 제28권3호
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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.

• 대한산업공학회지
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• 제33권1호
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• pp.33-43
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• 2007

The pickup and delivery problem with time windows generally involves the construction of optimal routeswhich satisfy a set of transportation requests under pairing, precedence, time window, vehicle capacity, andavailability constraints. In this paper, we added some constraints to the problem and adopted an objectivefunction based on number of used vehicles, total travel distance and total schedule duration to consider morerealistic problems. A branch and price algohthm for the problem is proposed and an enumeration method is usedfor the subproblems. The algorithm was tested on randomly generated instances and computational results werereported.

• 대한산업공학회지
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• 제23권2호
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• pp.275-288
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• 1997

The container transportation problem is a kind of generalized pickup and delivery problem(GPDP), and a typical NP-hard problem of which polynomial algorithm has not yet been developed. In this problem, trucks have to transport containers from origins to destinations, while have to satisfy several restrictions such as request time, cargo closing time, driver's break time. In this paper, we present a straightforward heuristic and a user-interactive truck dispatching system which supports decision makers.

• 한국항해항만학회지
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• 제29권3호
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• pp.221-226
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• 2005

본 연구는 화물 운송 문제에 GIS 기법을 응용하여 화물의 수거 및 배송문제를 개선한 논문이다. 최근 국내 물류업체들은 인터넷을 기반으로 주문, 검색 및 화물의 추적 등을 온라인상에서 실행토록 하는 방법을 중시하게 되었다. 국내외 배송 관련 기업들은 빠른 서비스를 요 구하는 긴급주문의 비중이 커 가는 시장변환에 대처해서, 서비스 능력의 향상과 효율적인 차량관리를 위해서 GPS와 TRS 등의 정보통신기술을 이용하여, 기업의 배차업무를 개선하려고 노력하고 있다. 하지만 아직까지 배차 담당자의 의사결정을 지원할 수 있는 배차기법에 대한 연구는 거의 이루어지지 않고 있는 것이 현 실정이다, 본 연구에서는 GIS기반 하에서의 거리산정방법을 제안하고 이를 이용하여 차량운송 및 수거계획 알고리즘을 개발하였다. 또한 본 연구에서는 차량 및 화물정보를 GIS환경에서 실시간으로 조회해 볼 수 있도록 하였으며, 입출력자료와 차량 및 화물정보 조회결과를 GIS환경에서 구현하도록 하였다. 사용자들을 위하여 GUI-type 프로그램을 개발하고 실 예제를 통하여 Sample 출력을 보였다. 본 연구의 결과는 추후 약간의 수정 보완을 통하여 실제 물류센터에서의 운송계획 작성시 바로 적용할 수 있을 것이라고 판단된다.

• Management Science and Financial Engineering
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• 제18권1호
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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.

• Advances in aircraft and spacecraft science
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• 제10권5호
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• pp.393-418
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• 2023

Drones are increasingly used in logistics delivery due to their low cost, high-speed and straight-line flight. Considering the small cargo capacity, limited endurance and other factors, this paper optimized the pickup and delivery vehicle routing problem with time windows in the mode of "truck+drone". A mixed integer programming model with the objective of minimizing transportation cost was proposed and an improved adaptive large neighborhood search algorithm is designed to solve the problem. In this algorithm, the performance of the algorithm is improved by designing various efficient destroy operators and repair operators based on the characteristics of the model and introducing a simulated annealing strategy to avoid falling into local optimum solutions. The effectiveness of the model and the algorithm is verified through the numerical experiments, and the impact of the "truck+drone" on the route cost is analyzed, the result of this study provides a decision basis for the route planning of "truck+drone" mode delivery.

• 산업경영시스템학회지
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• 제44권2호
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• pp.36-42
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• 2021

This paper deals with a vehicle routing problem with resource repositioning (VRPRR) which is a variation of well-known vehicle routing problem with pickup and delivery (VRPPD). VRPRR in which static repositioning of public bikes is a representative case, can be defined as a multi-objective optimization problem aiming at minimizing both transportation cost and the amount of unmet demand. To obtain Pareto sets for the problem, famous multi-objective optimization algorithms such as Strength Pareto Evolutionary Algorithm 2 (SPEA2) can be applied. In addition, a linear combination of two objective functions with weights can be exploited to generate Pareto sets. By varying weight values in the combined single objective function, a set of solutions is created. Experiments accomplished with a standard benchmark problem sets show that Variable Neighborhood Search (VNS) applied to solve a number of single objective function outperforms SPEA2. All generated solutions from SPEA2 are completely dominated by a set of VNS solutions. It seems that local optimization technique inherent in VNS makes it possible to generate near optimal solutions for the single objective function. Also, it shows that trade-off between the number of solutions in Pareto set and the computation time should be considered to obtain good solutions effectively in case of linearly combined single objective function.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2001년도 추계학술대회 논문집
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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.

• 경영과학
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• 제33권1호
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• pp.89-99
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• 2016

A scheduled airlift is the most critical part of the air transportation operations in ROK Air Force. The military cargo-plane routing problem is a PDPLS (pickup and delivery problem in which load splits and node revisits are allowed). The cargo which is transported by a military cargo-plane is measured in pallet. The efficiency of pallet needs to be considered with respect to its volume and weight. There are some guidelines about orders of priorities and regulations in the military air transportation. However, there are no methodologies which can raise the efficiency of flight scheduling using Operations Research (OR) theories. This research proposes the effective computing methodology and the related heuristic algorithms that can maximize the effectiveness of the path routing model.

• 한국경영과학회지
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• 제31권2호
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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.