• Spatial Information Research
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• v.18 no.3
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• pp.63-72
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• 2010

The vehicle routing problem with simultaneous pick-up and delivery (VRPSPD) is a variant of the vehicle routing problem (VRP) that customers require simultaneously a pick-up and delivery service. The main objective of VRPSPD is to minimize a cost of routes satisfying many constraints. Traditional VRPSPD have been dealt with a static environment. The static environment means that a routing data and plan cannot be changed. For example, it is difficult to change a vehicle's routing plan so that a vehicle serves the pick-up demands of new customers during the delivery service. Therefore, traditional approach is not suitable for dynamic environments. To solve this problem, we propose a novel approach for finding efficient routes using a real-time re-routing heuristics based on the Location Based Service (LBS). Our re-routing heuristics can generate a new route for vehicle that satisfies a new customer's demand considering the current geographic location of a vehicle. Experimental results show that our methodology can reduce the traveling cost of vehicles comparing with other previous methods.

• Journal of the Korea Society for Simulation
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• v.16 no.1
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• pp.39-47
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• 2007

The travel speed between two locations within the downtown differs according to time horizon and district. Also, There is delay time on numerous traffic signals and bottle neck areas. It has an influence on planning the vehicle routing. However, there are almost no studies focusing on delay time for distance and travel time between two locations among the existing researches for vehicle routing problem (VRP). In this paper, we approach the real VRP by designing the model which estimates the delay time for traffic signal and bottle neck areas. The results of computation experiment demonstrate that proposed method performs well and have better solution than other method not considering the delay time.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.10a
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• pp.279-282
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• 2000

물류시스템설계 및 개선의 일환으로 차량운송계획 문제는 매우 중요시되는 분야이다. 본 연구는 유전자 알고리즘을 이용한 통합물류 운송계획문제(Integrated Vehicle Routing Problem : IVRP)를 위한 전산화 모델의 개발로서 운송 중인 차량의 자동위치 조회시스템(Automatic Vehicle Location System : AVL)을 이용하여 차량운송의 통제기능을 높이며, 차량운송 효율을 높이는 목적으로 VRP문제와 AVL문제를 연계하는 통합운송시스템의 개념 연구이다. 본 연구에서는 다-물류센터를 고려한 운송 영역할당(Sector Clustering), 경로계획 문제(VRP) 및 유전자 알고리즘을 이용한 운송순서 계획(GA-TSP)을 고려한 통합운송계획모델의 개발을 목적으로 차량의 운송간의 통신 및 통제 등의 기능을 위하여 위치 추적을 가진 GPS와 통신시스템을 위한 TRS 및 위치설정을 위한 GIS를 고려하였다. 본 연구에서의 AVL시스템 개발을 위한 GPS, GIS 및TRS 등 AVL시스템의 구성요소에 대하여 그 개요를 조사 연구하였다. 또한 GPS, GIS을 기반으로한 물류시스템의 구성과 시스템에 필요한 기능 및 구성요소를 파악하고 서브 시스템을 구성하여 각 서브 시스템의 기본설계를 실시하기 위한 연구이다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.179-184
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• 2002

We consider the heterogeneous fleet vehicle routing problem (HVRP), a variant of the classical vehicle routing problem (VRP). The HVRP differs from the classical VRP in that it deals with a heterogeneous fleet of vehicles having various capacities, fixed costs, and variables costs. Therefore the HVRP is to find the fleet composition and a set of routes with minimum total cost. We give an integer programming formulation of the problem and propose an algorithm to solve it. Although the formulation has exponentially many variables, we can efficiently solve the linear programming relaxation of it by using the column generation technique. To generate profitable columns we solve a shortest path problem with capacity constraints using dynamic programming. After solving the linear programming relaxation, we apply a branch-and-bound procedure. We test the proposed algorithm on a set of benchmark instances. Test results show that the algorithm gives best-known solutions to almost all instances.

• Journal of the military operations research society of Korea
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• v.24 no.2
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• pp.117-129
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• 1998

This study is concerned with developing a heuristic for a web-based vehicle routing problem using mixed genetic algorithm(VRPMGA) which determines each vehicle route in order to minimize the transportation costs, subject to meeting the demands of all delivery points. VRP is known to be NP-hard, and it needs a lot of computing time to get the optimal solution, so that heuristics are more frequently developed than optimal algorithms. This study aims to develop a mixed genetic algorithm by partitioned strategy which can give a good solution in comparatively brief time. The good features of the VRPMGA are, fristly, the ability of early convergence and, secondly, the capability of producing multiple, alternative, and near-optimal solutions. The VRPMGA is a useful algorithm that can be appliable to VRP and TSP. Finally, the computational test were performed using the benchmark problems and the proposed heuristic is compared with the other existing algorithms (COSA). The result of computational tests shows that proposed heuristic gives good solutions, in much shorter time, which are same as the best known solutions in the pervious research.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.3
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• pp.325-336
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• 1996

This study is concerned with developing a heuristic for the vehicle routing problem(VRP) which determines each vehicle route in order to minimize the transportation costs, subject to meeting the demands of all delivery points. VRP is known 10 be NP-hard, and it needs a lot of computing time to get the optimal solution, so that heuristic are more frequently developed than optimal algorithms. This study aims to develop a heuristic which can give a good solution in comparatively brief time. Finally, the computational tests were performed using the benchmark problems and the proposed heuristic is compared with the other existing algorithms. The result of computational tests shows that the proposed heuristic gives good solutions, in much shorter time, which are not 1% more expensive than the best known solutions, which are same as the best known solutions in the previous researches.

• Korean Management Science Review
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• v.24 no.2
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• pp.43-56
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• 2007

VRP(Vehicle Routing Problem) is studied in this paper, where two different kinds of missions are to be completed. The objective is to minimize the total vehicle operating distance. A mixed integer programming formulation and a heuristic algorithm for a practical use are suggested. A heuristic algorithm consists of three phases such as clustering, constructing routes, and adjustment. In the first phase, customers are clustered so that the supply nodes are grouped with demand nodes to be served by the same vehicle. Vehicle routes are generated within the cluster in the second phase. Clusters and routes are adjusted in the third phase using the UF (unfitness) rule designed to determine the customers and the routes to be moved properly. It is shown that the suggested heuristic algorithm yields good performances within a relatively short computational time through computational experiment.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2009.06a
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• pp.171-172
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• 2009

Generally, the container road transportal ion am be divided into three types; short distance, long distance and shuttle transportation. Also container vehicle am be divided into three types according to the chassis types of vehicle; only 20-feet container, only 40-feet container, combined chassis trailer. This paper deals with Vehicle Routing Problem(VRP) for delivering containers considering shuttle transportation. The shuttle service occurs several amounts of container which is same as O/D pairs. This problem is similar to the previously studied VRP for delivering containers using combined chassis trailers, but the characteristics of shuttle service must be considered additionally. We formulate the container shuttle transportation planning problem using combined chassis trailers based on VRP with pick-up and delivery which can visit each node more than one time, and propose an efficient solution procedure.

• Journal of Distribution Science
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• v.10 no.12
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• pp.19-24
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• 2012

Purpose - This paper discusses the heterogeneous fixed fleet vehicle routing problem with pick-up and delivery (HFFVRPPD), for vehicles with different capacities, fixed costs, and travel costs. Research Design, data, methodology - This paper made nine assumptions for establishing a mathematical model to describe HFFVRPPD. It established a practical mathematical model, and because of the non-deterministic polynomial-time hard (NP-hard), improved the traditional simulated annealing algorithm and tested a new algorithm using a certain scale model. Result - We calculated the minimum cost of the heterogeneous fixed fleet vehicle routing problem (HFFVRP) with a single task and, on comparing the results with the actual HFFVRP for the single task alone, observed that the total cost of HFFVRPPD reduced significantly by 46.7%. The results showed that the new algorithm provides better solutions and stability. Conclusions - This paper, by comparing the HFFVRP and HFFVRPPD results, highlights certain advantages of using HFFVRPPD in physical distribution enterprises, such as saving distribution vehicles, reducing logistics cost, and raising economic benefits.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.485-488
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• 2000

실제 많은 차량경로결정문제(Vehicle Routing Problem: VRP)에서 차량의 이동속도는 도로의 교통량 등의 인에 의해 시간에 따라 변화하고 서비스 수량이 고객의 운영상태에 따라 달라질 수 있다. 이러한 사실에도 불구하고, 거의 대부분의 VRP 기법에서 차량속도와 서비스 수량을 확정적으로 가정하거나 평균값을 사용하는 이유는 알고리즘 적 분석의 어려움 때문인 것으로 알려져 있다. 이에 따라 확정적 VRP 기법들에 해 구해진 해는 실제 적용에서 그 유효성에 대해 심각한 이의가 제기될 수 있다. 그러나 만일 잘 알려진 정적 VRP 기법들이 확률적 상황에서도 뛰어난 성능을 보인다면, 실제 차량경로계획 상황에서 이들 확정적 기법들이 복잡하고 난해한 확률적 VRP 기법을 대신할 수 있을 것이다. 본 논문에서는 확률적 환경에서 네 가지 확정적 VRP 기법들의 성능을 평가하는 계산실험 연구를 소개한다. Solomon의 다양한 실험문제를 사용하였으며, 모든 문제에서 hard 및 soft 서비스 시간대를 설정하였다. 그리고 지점간 차량이동시간과 고객들의 서비스 물량은 세 가지 확률분포로써 나타내었다. 실험결과, 특정 확정적 VRP 기법이 특정 확률적 환경에서 뛰어난 성능을 보이는 것을 확인할 수 있었다