• Journal of the military operations research society of Korea
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• v.12 no.2
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• pp.37-55
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• 1986

Vehicle fleet planning problem is generic name given to a whole class of practical decision making problems which find the vehicle routes and schedules to accomplish the reqired service to customers using vehicles. In this paper the various problems are classified into the three groups according to their characteristics: (1) vehicle routing problems, (2) vehicle scheduling problems, and (3) vehicle routing and scheduling problems. The State of the art of each group is described and the future research directions are presented.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.4
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• pp.719-728
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• 1997

In the AGV routing a vehicle can select the shortest route on which no conflicts are anticipated. The procedure includes time constraint and the node/arc occupation times of vehicles in order to locate the conflicting paths. The slight differences among AGV routing algorithms exist in identifying the conflict regions encountered while reaching out to the destination node. In this paper, a novel approach to the use of the re-routing scheme is presented. It will be used to minimize the travel distance of vehicles in a regular vehicle routing process rather than to cope with emergency situations. The proposed algorithm provides existing active vehicles with the ability of changing their current paths for a new vehicle whenever the equal-distance paths exist, in on attempt to optimize the AGV transportation system. This ability is possible because of the flexibility of on AGV system controlled by a computer system.

• Korean Management Science Review
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• v.29 no.1
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• pp.89-99
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• 2012

In this paper, we deal with the dual-depot heterogeneous vehicle routing problem with simultaneous delivery and pick up(DH-VRPSDP) in reverse logistics. The DH-VRPSDP is a problem of designing vehicle routes in a day of given vehicle to minimize the sum of fixed cost and variable cost over the planning horizon. Each customer can be visited only once 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 changing the customer and the vehicle simultaneously and then it is improved. A performance of the proposed algorithm was compared to both well-known results and new test problems.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1740-1745
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• 2006

This paper is concerned with a novel heuristic algorithm for the multi-trip vehicle routing problem with time windows. The objective function is the minimization of total vehicle operating time, fixed cost of vehicle and the minimization of total lateness of customer. A mixed integer programming formulation and a heuristic algorithm for a practical use are suggested. A heuristic algorithm is constructed two phases such as clustering and routing. Clustering is progressed in order to assign appropriate vehicle to customer, and then vehicle trip and route are decided considering traveling distance and time window. It is shown that the suggested heuristic algorithm gives good solutions within a short computation time by experimental result.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.167-178
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• 2019

In this paper, we study the multi-objectives vehicle and drone routing problem with time windows, MOVDRPTW for short, which is defined in an urban delivery network. We consider the dual modal delivery system consisting of drones and vehicles. Drones are used as a complement to the vehicle and operate in a point to point manner between the depot and the customer. Customers make various requests. They prefer to receive delivery services within the predetermined time range and some customers require fast delivery. The purpose of this paper is to investigate the effectiveness of the delivery strategy of using drones and vehicles together with a multi-objective measures. As experiment datasets, we use the instances generated based on actual courier delivery data. We propose a hybrid multi-objective evolutionary algorithm for solving MOVDRPTW. Our results confirm that the vehicle-drone mixed strategy has 30% cost advantage over vehicle only strategy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5322-5342
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• 2016

In vehicle-to-vehicle (V2V) networks, where selfishness degrades node activity, countermeasures for collaboration enforcement must be provided to enable application of a sage and efficient network environment. Because vehicular networks feature both high mobility and various topologies, selfish behavior judgment and establishment of a stable routing protocol become intensely challenging. In this paper, a two-phase-based generous cooperative routing protocol (called GEC) is presented for V2V networks to provide resistance to selfishness. To detect selfish behaving vehicles, a packet forwarding watchdog and an average connection rate based on the multipath weight method are used, where evidence is gathered from different watchdogs. Then, multihop relay decisions are made using a generous cooperative algorithm based on game theory. Finally, through buffering of the multiple end-to-end paths and judicious choice of optimal cooperative routes, route maintenance phase is capable of dealing with congestion and rapidly exchanging traffic. Specifically, it is proved that the GEC is theoretically subgame perfect. Simulation results show that for V2V networks with inherently selfish nodes, the proposed method isolates uncooperative vehicles and is capable of accommodating both the mobility and congestion circumstances by facilitating information dissemination and reducing end-to-end delay.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.4
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• pp.43-50
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• 2010

Vehicle-to-Vehicle (V2V) is a special type of vehicle ad-hoc network (VANET), and known as a solution to provide communication among vehicles and reduce vehicle accidents. Geographical routing protocols as Greedy Perimeter Sateless Routing (GPSR) are very suitable for the V2V communication due to special characters of highway and device for vehicles. However, the GPSR has problem that appears local maximum by some stale neighbor nodes in the greedy mode of the GPSR. It can lose transmission data in recovery mode, even if the problem is can be solved by the recovery mode of the GPSR. We therefore propose a Greedy Perimeter Reliable Routing (GPRR), can provide more reliable data transmission, to resolve the GPSR problem in the V2V environment. Simulation results using ns-2 shown that the GPRR reveals much better performance than the GPSR by remarkably reducing the local maximum rate in the greedy mode.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1248-1251
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• 2002

Logistics optimization problems related with vehicle routing such as warehouse locating, track scheduling, customer order delivery, wastage pickup etc. are very interesting and important issues to date. Many Vehicle Routing and Scheduling Systems (VRSS) have been developed/proposed to optimize the logistics problems. But majority of them are dedicated to a particular problem and are unable to handle the real world spatial data directly. The system developed for one problem may not be suitable for others due to inter-problem constraint variations. The constraints may include geographical, environmental and road traffic nature of the working region along with other constraints related with the problem. So the developer always needs to modify the original routing algorithm in order to fulfill the purpose. In our study, we propose a general-purpose platform by combining GIS road map and Database Management System (DBMS), so that VRSS can interact with real world spatial data directly to solve different kinds of vehicle routing problems. Using the features of our developed system, the developer can frequently modify the existing algorithm or create a new one to serve the purpose.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.4
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• pp.346-354
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• 2004

Most industrial logistic systems have focused on carrying products from manufacturers or distribution centers to customers. In recent years, they are faced with the problem of integrating reverse flows into their transportation systems. In this paper, we address the vehicle routing problems with mixed delivery and pick-up(VRPMDP). Mixed operation of delivery and pick-up during a vehicle tour requires rearrangement of the goods on board. The VRPMDP considers the reshuffling time of goods at customers, hard time windows, and split operation of delivery and pick-up. We construct a mixed integer mathematical model and propose a new genetic algorithm named GAMP for VRPMDP. Computational experiments on various types of test problems are performed to evaluate GAMP against the modified Dethloff's algorithm. The results show that GAMP reduces the total vehicle operation time by 5.9% on average, but takes about six times longer computation time.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.53
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• pp.37-44
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• 1999

The problem to be studied here is the minimization of the total travel distance and the number of vehicles used for delivering goods to customers. Vehicle routes must also satisfy a variety of constraints such as fixed vehicle capacity, allowed operating time. Genetic algorithm to solve the VRPTW with heterogeneous fleet is presented. The chromosome of the proposed GA in this study has the 3-dimension. We propose GA that has the cubic-chromosome for VRPTW with heterogeneous fleet. The newly suggested ‘Cubic-GA (or 3-D GA)’ in this paper means the 2-D GA with GLS(Genetic Local Search) algorithms and is quite flexible. To evaluate the performance of the algorithm, we apply it to the Solomon's VRPTW instances. It produces a set of good routes and the reasonable number of vehicles.