• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1994.04a
• /
• pp.27-27
• /
• 1994

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2000.04a
• /
• pp.285-288
• /
• 2000

본 연구는 Heuristic 알고리즘 및 유전자알고리즘(GA)을 이용하여 수거(Pickup) 및 배달(Delivery)을 동시에 고려한 통합차량운송계획 모델의 개발이다. 본 연구는 기존의 TSP의 문제를 확장 응용하였으며, 이는 한 Route에서 수거지(Origin)와 운반지(Destination)를 포함하는 수요들을 만족하도록 운반되어야 하는 문제이다. 이러한 통합차량경로계획문제(VRP Vehicle Routing Problem)를 해결하기 위한 접근방법으로 Heuristic 방법을 사용하였으며, 기존의 Saving 알고리즘과 유전자알고리즘(Genetic Algorithm)의 각종 연산자(Operators)들을 계산하여 사용한 TSP문제의 해를 본 연구의 해의 초기해로 사용하였으며 수거 및 배달문제의 특성을 고려하여 해를 구하였다. 본 연구의 결과를 다양한 운송환경에서, 거리산정방법, 가용운송장비 대수, 운송시간의 제한, 물류센터 및 운송지점의 위치 및 수요량 등 다양한 인자들을 고려한 통합시스템으로 프로그램을 개발하고 Sample 문제를 통하여 응용결과를 보였다.

• Journal of Korean Society of Transportation
• /
• v.25 no.5
• /
• pp.161-172
• /
• 2007

Vehicles transporting hazardous materials can make huge damage to people, properties and environment by traffic accidents. Therefore, transporting hazardous materials is a big issue with the cutting edge technology of communications in these days. However, despite this situation, Korean government gives limited efforts for systematic management, research and investment about hazardous materials. Accordingly, this research suggests the key path finding algorithm about management of real-time schedule and routes for vehicles transporting hazardous materials. Besides, the case study is progressed in transportation networks of Seoul in order to evaluate the reality of algorithm. Specifically, time-space network transformation is performed for time window attributes. In addition, this study proposes the techniques searching for non-dominated paths considering schedule by the multiobjective shortest path algorithm based on dynamic programming in dynamic transportation networks including multiobjective attributes.

• Journal of Korean Society of Transportation
• /
• v.23 no.4 s.82
• /
• pp.81-91
• /
• 2005

The Traveling Salesman Problem(TSP) is one of the NP-complete (None-deterministic Polynomial time complete) route optimization problems. Its calculation time increases very rapidly as the number of nodes does. Therefore, the near optimum solution has been searched by heuristic algorithms rather than the real optimum has. This paper reviews the Ant System Algorithm(ANS), an heuristic algorithm of TSP and its applicability in the parcel delivery service in Korea. ASA, which is an heuristic algorithm of NP-complete has been studied by M. Dorigo in the early 1990. ASA finds the optimum route by the probabilistic method based on the cumulated pheromone on the links by ants. ASA has been known as one of the efficient heuristic algorithms in terms of its calculation time and result. Its applications have been expanded to vehicle routing problems, network management and highway alignment planning. The precise criteria for vehicle routing has not been set up in the parcel delivery service of Korea. Vehicle routing has been determined by the vehicle deriver himself or herself. In this paper the applicability of ASA to the parcel delivery service has been reviewed. When the driver s vehicle routing is assumed to follow the Nearest Neighbor Algorithm (NNA) with 20 nodes (pick-up and drop-off places) in $10Km{\times}10Km$ service area, his or her decision was compared with ASA's one. Also, ASA showed better results than NNA as the number of nodes increases from 10 to 200. If ASA is applied, the transport cost savings could be expected in the parcel delivery service in Korea.

• Management & Information Systems Review
• /
• v.29 no.4
• /
• pp.109-121
• /
• 2010

In this study, we propose a solution procedure to solve travelling salesman problem(TSP) with special cost function, route dependent travelling salesman problem(RDTSP). First, we develop an integer programming model to describe the problem. In the model, a variable means a possible route. And, the number of variables in this model are extremely large. So, we develop a LP relaxation problem of the IP model and solve the relaxation problem by a column generation technique. The relaxation problem does not guarantee the optimal solution. If we get an integer solution in the ralaxation problem, then the solution is an optimal one. But, if not, we cannot get an optimal solution. So, we approach a branch and price technique. The overall solution procedure can be applied a printed circuit board(PCB) assembly process.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2013.05a
• /
• pp.421-424
• /
• 2013

차량 애드 혹 네트워크는 도심 교차로에서 도로의 특성과 차량의 높은 이동성으로 인해 네트워크의 단절이 자주 일어난다. 향상된 지리기반 라우팅 프로토콜인 GBSR(Greedy Border Superiority Routing)은 V2V(Vehicle-to-Vehicle)에 적합하다. 그러나 탐욕모드에서 stale노드가 로컬최대에 직면하는 문제를 가지고 있다. EGBSR(Enhanced GBSR)은 반대 방향의 차량과 같은 방향의 차량에게 보내는 비콘 메시지와 도로 정보를 관리하는 테이블을 이용하여 경로를 탐색하고 설정된 경로를 통해 패킷을 보낸다. 이를 통해 소스노드가 목적지노드에 빠르고 안전하게 패킷을 전달할 수 있는 양방향 라우팅 기법 제안한다.

• Journal of Korean Society for Geospatial Information Science
• /
• v.25 no.2
• /
• pp.21-29
• /
• 2017

For the efficient and stable operation of autonomous vehicles or advanced driver assistance systems being actively studied nowadays, it is important to determine the positions of the vehicle accurately and economically. A satellite based navigation system is mainly used for positioning, but it has a limitation in signal blockage areas. To overcome this limitation, sensor fusion methods including additional sensors such as an inertial navigation system have been mainly proposed but the high sensor cost has been a problem. In this work, we develop a vehicle position estimation algorithm using in-vehicle sensors and a low-cost imaging sensor without any expensive additional sensor. We determine the vehicle positions using the velocity and yaw-rate of a car from the in-vehicle sensors and the position and attitude of the camera based on the single photo resection process. For the evaluation, we built a prototype system, acquired test data using the system, and estimated the trajectory. The proposed algorithm shows the accuracy of about 40% higher than an in-vehicle sensor only method.

• Journal of the Korean Society for Precision Engineering
• /
• v.16 no.8
• /
• pp.155-161
• /
• 1999

아이들 상태에서 차실 내에 불쾌감을 주는 매우 높은 크기의 소음이 발생하였다. 본 논문에서는 아이들 시 문제소음의 원인을 분석하고 저감하는데 필요한 관련이론의 적용과 이에 수반되는 데이터측정, 데이터처리 및 데이터 해석과정을 자세하게 기술하였다. 소음진동 측정 및 분석 결과 문제의 소음은 엔진의 회전 2.5차 성분을 가지고 구조기인소음이었다. 아이들 시 문제의 실내소음에 영향을 미치는 구조전달경로들의 기여도를 분석하기 위해 소음경로해석시험 및 모드시험을 실시하였다. 시험분석 결과에 따라 기여도가 놓은 배 기계 및 트랜스미션계의 진동 전달특성을 개선하므로써 만족할 수준의 소음 저감효과를 얻었다.

• Journal of Intelligence and Information Systems
• /
• v.15 no.1
• /
• pp.1-14
• /
• 2009

The Capacitated Vehicle Routing Problem (CVRP) is the problem that the vehicles stationed at central depot are to be optimally routed to supply customers with demands, satisfying vehicle capacity constraints. The CVRP is the NP-hard as it is a natural generalization of the Traveling Salesman Problem (TSP). In this article, we propose the heuristic algorithm, called the bisection seed detection method, to solve the CVRP. The algorithm is composed of 3-phases. In the first phase, we work out the initial cluster using the improved sweep algorithm. In the next phase, we choose a seed node in each initial cluster by using the bisection seed detection method, and we compose the rout with the nearest node from each seed. At this phase, we compute the regret value to decide the list of priorities for the node assignment. In the final phase, we improve the route result by using the tabu search and exchange algorithm. We compared our heuristic with different heuristics such as the Clark-Wright heuristic and the genetic algorithm. The result of proposed heuristic show that our algorithm can get the nearest optimal value within the shortest execution time comparatively.

• Proceedings of the KSR Conference
• /
• 2007.11a
• /
• pp.1731-1737
• /
• 2007

This paper considers subway routing problem. Given a schedule of train to be routed by a railway stock, the routing problem determines a sequence of trains while satisfying turnaround time and maintenance restrictions. Generally, the solution of routing problem is generated from set partition formulation solved by column generation method, a typical integer programming approach for train-set. However, we find the characteristics of metropolitan subway which has a simple rail network, a few end stations and 13 departure-arrival patterns. We reflect a turn-around constraint due to spatial limitations has no existence in conventional railroad. Our objective is to minimize the number of daily train-sets. In this paper, we develop two basic techniques that solve the subway routing problem in a reasonable time. In first stage, we formulate the routing problem as a Min-cost-flow problem. Then, in the second stage, we attempt to normalize the distance covered to each routes and reduce the travel distance using our heuristic approach. Applied to the current daily timetable, we could find the subway routings, which is an approximately 14% improvement on the number of train-sets reducing 15% of maximum traveling distance and 8% of the standard deviation.