• Proceedings of the Korea Society for Simulation Conference
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• 1999.10a
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• pp.114-120
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• 1999

본 연구는 Heuristic 알고리즘 및 유전자알고리즘(GA)을 이용하여 3단계의 통합차량운송계획 모델의 개발이다. 차량경로문제(VRP : Vehicle Routing Problem)를 해결하기 위한 접근방법으로 기존의 Saving 알고리즘을 개선하여 사용하였으며 유전자 알고리즘(Genetic Algorithm)의 각종 연산자 (Operators)들을 계산하여 사용하였다. 본 모델은 다음 3단계의 접근방법을 사용하였다 ; 1) 다 물류 센터의 문제해결을 위한 영역활당(Sector Clustering) 모델, 2) 경로계획모델(VRP Model), 및 3) 최적 운송계획모델(GA-TSP Model). 본 모델들을 다양한 운송환경에서, 거리산정방법, 가용운송장비 대수, 운송시간의 제한, 물류센터 및 운송지점의 위치 및 수요량 등 다양한 파라메터들을 고려한 통합시스템으로 3개의 Component로 구성된 GUI-Type 프로그램을 개발하고 Sample 응용결과를 보였으며 기존의 모델들 보다 우수한 결과를 보였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.314-317
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• 2010

본 연구는 차량 경로 스케줄링 문제(VRSPTW, the Vehicle Routing and Scheduling Problem with Time Window)를 해결하기 위하여, 멀티 비용 함수(Multi Cost Function)를 갖는 개미 군집 최적화(Ant Colony Optimization)을 이용한 휴리스틱을 제안하였다. 멀티 비용 함수는 각 개미가 다음 고객 노드로 이동하기 위해 비용을 평가할 때 거리, 요구량, 각도, 시간제약에 대해 서로 다른 가중치를 반영하여 우수한 초기 경로를 구할 수 있도록 한다. 본 연구의 실험결과에서 제안된 휴리스틱이 Solomon I1 휴리스틱과 기회시간이 반영된 하이브리드 휴리스틱보다 효율적으로 최근사 해를 얻을 수 있음을 보였다.

• Journal of the Korea Safety Management & Science
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• v.10 no.3
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• pp.217-225
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• 2008

The inventory routing problem (IRP) is an important area of Supply Chain Management. The objective function of IRP is the sum of transportation cost and inventory cost. We propose an Artificial Immune System(AIS) to solve the IRP. AIS is one of natural computing algorithm. An hyper mutation and an vaccine operator are introduced in our research. Computation results show that the hyper mutation is useful to improve the solution quality and the vaccine is useful to reduce the calculation time.

• Proceedings of the Korean DIstribution Association Conference
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• 2003.05a
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• pp.55-70
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• 2003

The most transport companies are placing increasing emphasis on powerful new techniques for planning their vehicle operations. They have tried to improve their vehicle control and customer service capability by adopting tile advanced information technology, such as GPS(Global Position System) and Using Digital Map. But researches on the VRSP(vehicle routing St schedule problem) in this situation were very few. The purpose of this research is to develop vehicle scheduling heuristics for making a real-time dynamic VRSP under the situation that GPS and using Digital Map are equipped to the transport company. Modified savings techniques are suggested for the heuristic method and an insertion technique is suggested for the dynamic VRSP. The urgent vehicle schedule is based on the regular vehicle schedule. This study suggest on VRSP system using GPS and Digital Map and the performance of the suggested heuristics is illustrated through an real case example.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.249-252
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• 2004

The automatic determination of vehicle operation status as well as continuous tracking of vehicle location with intelligent management is one of major elements to achieve the goals. Especially, vehicle operation status can only be analyzed in terms of expert experiences with real-time location data with scheduling information. However the scheduling information of individual vehicle is very difficult to be interpreted immediately because there are hundreds of thousand vehicles are run at the same time in the national wide range workplace. In this paper, we propose the location-based knowledge management system(LKMs) using the active trajectory analysis method with routing and scheduling information to cope with the problems. This system uses an inference technology with dispatching and geographic information to generate the logistics knowledge that can be furnished to the manager in the central vehicle monitoring and controlling center.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.1
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• pp.133-140
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• 2014

An efficient heuristic for two-vehicle-one-depot problems is developed in this research. Vehicle moving speeds are various along hour based time intervals due to traffic jams of rush hours. Two different heuristics are examined. One is that the delivery area assignment is made using Sweep algorithm for two vehicles by splitting the whole area in half to equally divide all delivery points. The other is using common area by leaving unassigned area between the assigned for two vehicles. The common area is reassigned by two stages to balance the completion time of two vehicle's delivery. The heuristic with common area performed better than the other due to various vehicle moving speeds and traffic jams.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.57-78
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• 2005

The vehicle routing problem (VRP) is to determine a set of feasible vehicle routes, one for each vehicle, such that each customer is visited exactly once and the total distance travelled by the vehicles is minimized. A feasible route is defined as a simple circuit including the depot such that the total demand of the customers in the route does not exceed the vehicle capacity. While there have been significant advances recently in exact solution methodology, the VRP is not a well solved problem. We find most approaches still relying on the branch and bound method. These approaches employ various methodologies to compute a lower bound on the optimal value. We introduce a new modelling approach, termed route-splitting, for the VRP that allows us to address problems whose size is beyond the current computational range of set-partitioning models. The route-splitting model splits each vehicle route into segments, and results in more tractable subproblems. Lifting much of the burden of solving combinatorially hard subproblems, the route-splitting approach puts more weight on the LP master problem, Recent breakthroughs in solving LP problems (Nemhauser, 1994) bode well for our approach. Lower bounds are computed on five symmetric VRPs with up to 199 customers, and eight asymmetric VRPs with up to 70 customers. while it is said that the exact methods developed for asymmetric instances have in general a poor performance when applied to symmetric ones (Toth and Vigo, 2002), the route splitting approach shows a competent performance of 93.5% on average in the symmetric VRPs. For the asymmetric ones, the approach comes up with lower bounds of 97.6% on average. The route-splitting model can deal with asymmetric cost matrices and non-identical vehicles. Given the ability of the route-splitting model to address a wider range of applications and its good performance on asymmetric instances, we find the model promising and valuable for further research.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.401-402
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• 2012

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1999.04a
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• pp.173-173
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• 1999

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.884-888
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• 2009

Vehicular Adhoc Networks (VANET), a Vehicle-to-Infrastucture or Vehicle-to-Vehicle communication technology, is an area that makes more specific use of Mobile Adhoc Networks(MANET). VANET's Quality of Service(QoS) focuses on preventing possible emergencies like car crash from happening by immediately transmitting information to the cars around, while MANET's QoS is being studied for the quality of multimedia data such as Video on Demand(VoD), Video streaming, Voice over IP(VoIP), etc. In this paper, I structure the actual network configuration using Link State Routing(LSR), implement QoS Provisioning Model using Common Open Policy Service(COPS), and suggest more effective k-hop Cluster and inter-domain policy negotiation which fit better to the characteristics of VANET.