• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.3
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• pp.63-79
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• 1994

Many vehicle fleet planning systems have been suggested to minimize the routing distances of vehicles or reduce the transportation cost. But the more considerations the method takes, the higher complexites are involved in a large number of practical situations. The purpose of this paper is to vehicle fleet planning system. This paper is considered multi-objective optimization. The vehicle fleet planning system developed by this study involves such complicated and restricted conditions as one depot, multiple nodes (demand points), multiple vehicle types, multipel order items, and other many restrictions for operating vehicles. The proposed algorithm is compared with the nearest neighbor heuristic (NNH) and the savings heuristic (SAH) algorithm in terms of total logistics cost and driving time. This method constructs a route with a minimum number of vehicles for a given demand. This method can be used to any companys which vehicle fleet planning system under circumstances considered in this paper.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.4
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• pp.396-410
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• 2012

The purpose of this study is to quantify the contribution of high emitting vehicles to mobile emission inventories. Analyzed emission data include $NO_x$, HC, and CO results, which were measured through the vehicle Inspection and Maintenance (I/M) program in Seoul metropolitan area. The high emitting vehicles were identified as the top 5% worst polluting cars of the fleet. We estimated that 5% of the gasoline passenger car fleet, which is high emitters, generated 25.5% of $NO_x$, 34.5% of HC, and 66.1% of CO emissions of total inventories for gasoline passenger car fleet in year 2010. In the study, we identified that the older vehicles (older than ten years) and high mileage vehicles (more than 120,000 km driven) comprised high emitter fleet with 70.9% and 71.2%, respectively. The emission contribution of high emitters became larger in younger fleet than in the older fleet. This is due to the reduced emission rates in newly manufactured vehicles, which were developed under the more stringent emission regulation limits. This analysis implies that high emitters could be responsible for an even larger fraction of total vehicular emissions as more advanced technology vehicles are being incorporated into the current vehicle fleet. The findings suggested that the high emitting vehicles should be primarily considered for in-use vehicle emission management program, such as I/M, accelerated vehicle retirement, or catalytic converter replacement, in order to enhance the effectiveness of selected program.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.10a
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• pp.171-174
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• 2000

This paper presents an approach to determine the vehicle fleet size for container shuttle service in a stochastic working environment. The shuttle service can be defined as the repetitive travel between the designated places during working period. The initial number of vehicles is temporarily calculated using the transportation model. Simulation is carried out in order to investigate dynamic behavior of container shuttle. Finally, the equation for estimating the vehicle fleet size is obtained through the multiple regression model based on simulation results.

• International Journal of Reliability and Applications
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• v.12 no.2
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• pp.95-102
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• 2011

This paper uses the auto regression model to modeling failure number of a bus fleet. The fitted model can be used to predict the failure number in the future. A numerical example is presented to illustrate the modeling process and the appropriateness of the fitted model. At last, some possible applications of the model are discussed.

• 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.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.209-215
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• 2002

In this paper, we propose a freight and fleet optimization model under CVO environment. The model is a kind of multi commodity network flow model based on Vehicle Routing Problem(VRP) and Vehicle Scheduling Problem(VSP), and considering operations and purposes of CVO. The main purpose of CVO is the freight and fleet management to reduce logistics cost and to Improve in vehicle safety. Thus, the objective of this model is to minimize routing cost of all the vehicle and to find the location of commodities which have origin and destination. We also present some computing test results.

• Journal of the Korean Operations Research and Management Science Society
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• v.36 no.1
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• pp.27-38
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• 2011

In this paper, we deal with the periodic heterogeneous fleet vehicle routing problem (PHVRP). PHVRP is a problem of designing vehicle routes in each day of given period to minimize the sum of fixed cost and variable cost over the planning horizon. Each customer can be visited once or more times over the planning horizon according to the service combinations of that customer. Due to the complexity of the problem, we suggest a heuristic algorithm in which an initial solution is obtained by assigning the customer-day and the customer-car simultaneously and then it is improved. A performance of the proposed algorithm was compared to both well-known results and new test problems.

• Korean Management Science Review
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• v.17 no.2
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• pp.87-95
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• 2000

This paper presents two analytical approaches to determine the vehicle fleet size for container shuttle service. The shuttle service can be defined as the repetitive travel between the designated places during working period. In the first approach, the transportation model is adopted in order to determine the number of vehicles required. Its advantages and disadvantages in practical application are also discussed. In the second approach, a logical network which is oriented on job is transformed from a physical network which is focused on demand site. Nodes on the logical network represent jobs which include loaded travel, loading and unloading and arcs represent empty travel for the next jobs which include loaded travel, loading and unloading and arcs represent empty travel for the next job. Then a mathematical formulation is constructed similar to the multiple traveling salesman problem (TSP). A solution procedure is carried out based on the well-known insertion heuristic with the real world data.

• Journal of Korean Society of Transportation
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• v.22 no.2 s.73
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• pp.145-154
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• 2004

The growing demand for customer-responsive, made-to-order manufacturing is stimulating the need for improved dynamic decision-making processes in commercial fleet operations. Moreover, the rapid growth of electronic commerce through the internet is also requiring advanced and precise real-time operation of vehicle fleets. Accompanying these demand side developments/pressures, the growing availability of technologies such as AVL(Automatic Vehicle Location) systems and continuous two-way communication devices is driving developments on the supply side. These technologies enable the dispatcher to identify the current location of trucks and to communicate with drivers in real time affording the carrier fleet dispatcher the opportunity to dynamically respond to changes in demand, driver and vehicle availability, as well as traffic network conditions. This research investigates key aspects of real time dynamic routing and scheduling problems in fleet operation particularly in a truckload pickup-and-delivery problem under various settings, in which information of stochastic demands is revealed on a continuous basis, i.e., as the scheduled routes are executed. The most promising solution strategies for dealing with this real-time problem are analyzed and integrated. Furthermore, this research develops. analyzes, and implements hybrid algorithms for solving them, which combine fast local heuristic approach with an optimization-based approach. In addition, various partitioning algorithms being able to deal with large fleet of vehicles are developed based on 'divided & conquer' technique. Simulation experiments are developed and conducted to evaluate the performance of these algorithms.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1999.04a
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• pp.15-16
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• 1999