The growing logistics strategy of a company is to optimize their vehicle route scheduling in their supply chain system. It is very important to analyze for continuous pickups and delivery vehicle scheduling. This paper is a computational study to investigate the effectiveness of continuous pickups and delivery vehicle routing problems. These scheduling problems have 3 subproblems; Inbound Vehicle Routing Problem with Makespan and Pickup, Line-haul Network Problem, and Outbound Vehicle Routing Problem with Delivery. In this paper, we propose 5 heuristic Algorithms; Selecting Routing Node, Routing Scheduling, Determining Vehicle Type with Number and Quantity, and Modification Selecting Routing Node. We apply these Algorithms to S vehicle company. The results of computational experiments demonstrate that proposed methods perform well and have better solutions than other methods considering the basic time and due-date.

Logistics cost of domestic company has been improved continuously and annually, it is still higher than other main comparative countries. So, in this study, as optimizing the logistic network of distribution, it was trying to find methods decreasing logistics cost and storage cost, which occupies 86% of logistics cost of companies. through the efficiency of transportation and delivery routing, it could be also possible to decrease the logistics cost. And, it is also checked to find the logistics cost could be decreased by 10% by optimizing the routes of transportation and delivery, improving the transportation mode, etc.

A possible heuristic to solve metropolitan area vehicle routing problems with variable vehicle speeds is suggested in this research. Delivery hours are classified into 4 different time zones to make variable vehicle speeds no change within the same time zone to make TDVRP simple to solve. The suggested heuristic consists of 2 stages such as initial solution development step and initial solution improvement step. A computer program using C++ is constructed to evaluate the suggested heuristic. Randomly generated vehicle routing problems are used for the experiments. This heuristic could be helpful to logistics companies by increasing delivery efficiencies since the 4 zone classification is taken from the observed traffic information offered by a local government.

Recently, there are environmental issues for sustainable transportation system to pursue the energy-efficient and environment-friendly public urban transit. These transportation system needs to offer demand-oriented high-quality service being on the same level with cab service for urban space. PRT(Personal Rapid Transit), small track-guided vehicle, is repeatedly mentioned as a possible alternative for the new urban public transportion system, but but there are not many researches on the operational optimal routing for PRT network. In this paper, the concept of PRT and general optimal routing methods are reviewed. And we suggest the optimal routing method for city-wide PRT network with multi-vehicles and stations, junctions and directional arcs. Futher research directions for PRT routing are presented.

The large-scale disasters occur to unexpected accidents such as natural disasters(earthquake, typhoon, tsunami, etc.), and human-caused accidents(fire, collapse, terror etc.). Rescue teams perform rescue activities to save many lives in large-scale disaster area. The main purpose of this study is to compose a optimal routing planning for rescue of multiple victims in disaster area. A realistic routing planning with rescue limit time which considers rehabilitation and reconstruction will be suggested in this study. A mathematical programming model and a hybrid genetic algorithm will be suggested to minimize the total spending time. By comparing the result, the suggested algorithm gives a better solution than existing algorithms.

The types and quantities of Hazmat and Hazmat transportation are gradually increasing, keeping pace with industrialization and urbanization. At present the safety management for Hazmat transportation only considers reducing accident probability, but even when an accident involving Hazmat-carrying vehicles occurs, that is not regarded as a Hazmat-related accident if the Hazmats do not leak out from the containers carrying them. Thus the methods to reduce risk (Risk=Probability×Consequence) have to be developed by incorporating accident probability and consequence. By using Geographic Information System (GIS), a technical method is invented and is automatically able to evaluate the consequence by different types of Hazmat. Thus this study analyzed the degree of risk on the links classified by the Hazmat transport pathways. In order to mitigate the degree of risk, a method of 7-step risk management on Hazmat transportation in railway industries can be suggested. (1st step: building up GIS DB, 2nd step: calculating accident probability on each link, 3rd step: calculating consequence by Hazmat types, 4th step: determination of risk, 5th step: analysis of alternative plans for mitigating the risk, 6th: measure of effectiveness against each alternative, and 7th step: action plans to be weak probability and consequence by the range recommended from ALARP). In conclusion, those 7 steps are used as a standardization method of optimum transportation routing. And to increase the efficiency of optimum transportation routing, optional route can be revise by verification.

We developed two heuristic methods to solve the problem considering a fleet of ships delivering chemical products from terminals We need to decide how much of each product to carry, on which ship, subject to the conditions that all terminals must have suf

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.

  기간차량경로 문제는 차량용량제약을 고려한 차량경로문제를 다 기간으로 확장한 형태의 문제로 역방향 로지스틱스의 폐기물 혹은 재활용품 수거에 관련된 주요한 운영 문제들 중의 하나로 각 고객에 대해서는 계획기간 중에 방문해야 하는 횟수가 정해져 있어 방문날짜 조합을 결정해야 하며 주어진 방문날짜 조합 하에 각 기간의 차량경로도 결정해야 한다. 주요한 제약조건으로는 차량의 용량제약과 각 기간의 가용 시간제약이 있으며 소요차량의 대수를 최소화하는 것을 목적으

  본 논문은 시간 제약을 갖는 차량 라우팅 문제를 해결하기 위해 유전자 알고리듬과 부분 최적화 알고리듬을 적용한 방법을 소개한다. 유전자 알고리듬에서의 염색체는 노드를 나타내는 정수의 순열로 표현되어 직접적인 해를 나타내지 않지만, 경험적 방법에 의한 해석을 통해 유효한 해로 변형되도록 하였다. 유전자 알고리듬에 의해 생성된 주어진 수의 우수한 해들에는 세 부분 최적화 방법이 순차적으로 적용되어 보다 좋은 해를 생성하도록 하였다. 부분 최적화 방법들에

During last two decades the transportation system has developed into very intelligent system with GIS, GPS and ITS. The practical transportation management system provides real time response module to manage the customer's order. We have surveyed research papers on the real time vehicle routing problem in last two decades to figure out the dynamic vehicle routing problem. The papers are classified by basic routing algorithms and by managing the dynamic events which are the order management, the routing re-optimization, the routing post-optimization and the waiting strategy.

The vehicle routing problem determines each vehicle routes to find the transportation costs, subject to meeting the customer demands of all delivery points in geography. Vehicle routing problem 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 heuristic method which combines guided local search with a tabu search in order to minimize the transportation costs for the vehicle routing assignment and uses ILOG programming library to solve. The computational tests were performed using the benchmark problems. And computational experiments on these instances show that the proposed heuristic yields better results than the simple tabu search does.

As the use of vehicle route application and LBS(location based service) are fast grew, the importance of maintaining road network data is also increased. To maintain road data accuracy, we can collect road data by driving real roads with probe vehicle, or using digital image processing for the extraction of roads from aerial imagery. After compare the new road data to current database, we can update the road database, but that job is mostly time and money consuming or can be inaccurate. In this paper, an updating method of using GPS(global positioning system) enabled cell phone is proposed. By using GPS phone, we can update road database easily and sufficiently accurately.

As the use of vehicle route application and LBS (location based service) are fast grew, the importance of maintaining road network data is also increased. To maintain road data accuracy, we can collect road data by driving real roads with probe vehicle, or using digital image processing for the extraction of roads from aerial imagery. After compare the new road data to current database, we can update the road database, but that job is mostly time and money consuming or can be inaccurate. In this paper, an updating method of using GPS (global positioning system) enabled cell phone is proposed. By using GPS phone, we can update road database easily and sufficiently accurately.

  In this paper, we propose sludge collection strategies which allocate each sewage store of village to sewage treatment plants and decide the schedule of sludge collection in order to collect sludge efficiently. The strategies aim to decrease transportat

  The main objective of this study is to find out the shortest path of the vehicle routing problem with time window constraints by using both genetic algorithm and heuristic. Hard time constraints were considered to the vehicle routing problem in this sug

  Vehicle routing problem with time windows is determined each vehicle route in order to minimize the transportation costs. All delivery points in geography have various time restriction in camparision with the basic vehicle routing problem. Vechicle rout

광양항은 부산항과 더불어 우리나라 컨테이너 화물 처리 Two Port System의 한축으로 개발 중인 동북아 중심항만(Hub Port)으로서 향후 2011년까지 총 33개의 컨테이너 선적 등이 개발 추진 중에 있어 해상교통량이 급격히 증가하고 있으며, 또한 거대선·위험화물운반선·고속여객선의 통항이 빈번하여 대형사고의 발생우려가 상존하고 있다. 본 연구에서는 광양항을 이용하는 선박의 입출항 항로 등에 대한 해상교통환경을 면밀히 분석·평가하고, 통항로 및 항행보조시설 등의 적정성 검토를 통하여 미래 지향적이고 안전한 해상교통환경을 조성하기 위한 체계적이고 종합적인 항로를 설정한다.

Vehicle routing problem with Time Windows is determined each vehicle route in order to minimize the transportation costs. All delivery points in geography have various time restriction in camparision with the basic Vehicle routing problem. Vechicle routing problem with Time Windows 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 heuristic method which combines guided local search with a Tabu Search in order to minimize the transportation costs for the vehicle routing assignment and uses ILOG programming library to solve. The computational tests were performed using the benchmark problems.