• Title/Summary/Keyword: Vehicle Routing

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Design of the Simulation-Based Vehicle Distribution Planning System for Logistics (시뮬레이션을 이용한 물류 배송계획 시스템 개발에 관한 연구)

  • Yang, Byung-Hee;Lee, Young-Hae
    • IE interfaces
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    • v.7 no.2
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    • pp.87-97
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    • 1994
  • Many vehicle routing methods have been suggested, which minimize the routing distances of vehicles to reduce the total 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 develop a vehicle distribution planning system using heuristic algorithms and simulation techniques for home electronics companies. The vehicle distribution planning system developed by this study involves such complicated and stochastic conditions as one depot, multiple nodes(demand points), multiple vehicle types, multiple order items, and other many restrictions for operating vehicles. The proposed system is compared with the nearest neighbor method of the current system in terms of total logistics cost and driving time. This heuristics algorithm and simulation based distribution planning system is efficient in computational complexity, and give improved solutions with respect to the cost as well as the time. This method constructs a route with a minimum number of vehicles for a given demand.

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A Simulation Based Vehicle Distribution Planning System

  • 양병희;이영해
    • Journal of the military operations research society of Korea
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    • v.22 no.2
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    • pp.182-199
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    • 1996
  • Many vehicle routing methods have been suggested, which minimize the routing distances of vehicles to reduce the total 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 develop a vehicle distribution planning system using heuristic algorithms and simulation techniques for home electronics companies. The vehicle distribution planning system developed by this study involve so complicated and stochastic conditions such as one depot, multiple nodes(demand points), multiple vehicle types, multiple order items, and other many restrictions for operating vehicles. The proposed system is compared with the nearest neighbor method and the savings method in terms of total logistics cost and driving time. This heuristic algorithm and simulation based distribution planning system is efficient in computational complexity, and give improved solutions with respect to the cost as well as the time. This method constructs a route with a minimum number of vehicles for a given demand.

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Performance Analysis of GeoRouting Protocol in Vehicle Communication Environment (차량 통신 환경에서GeoRouting 프로토콜 성능 분석)

  • An, Sung-Chan;Lee, Joo-Young;Jung, Jae-Il
    • Journal of IKEEE
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    • v.18 no.3
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    • pp.427-434
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    • 2014
  • The Multihop Routing of vehicle communication environment is difficult to maintain due to heavy fluctuation of network topology and routing channel according to the movement of the vehicle, road property, vehicle distribution. We implemented GeoNetworking on the basis of ETSI(European Telecommunication Standard Institute) to maintain the vehicle safety service. GeoNetworking has its own way that delivers the data through the Unicast and Broadcast. In this paper, we compared performance index such as packet delivery ratio, end-to-end delay about GeoNetworking using the QualNet Network Simulator. Previous research assessed performance of GeoUnicast. This research has been additionally performed about GeoBroadcast, and we progressed algorithm performance through the comparison of CBF(Contention based Forwarding) of GeoUnicast with Greedy forwarding of GeoBroadcast.

The Bisection Seed Detection Heuristic for Solving the Capacitated Vehicle Routing Problem (한정 용량 차량 경로 탐색 문제에서 이분 시드 검출 법에 의한 발견적 해법)

  • Ko, Jun-Taek;Yu, Young-Hoon;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.15 no.1
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    • pp.1-14
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    • 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.

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Improved Intelligent Routing Protocol in Vehicle Ad-hoc Networks (차량 Ad-hoc 혹 통신에서 개선된 지능형 경로 프로토콜)

  • Lee, Dong Chun
    • Convergence Security Journal
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    • v.21 no.1
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    • pp.129-135
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    • 2021
  • Greedy protocols show good performance in Vehicular Ad-hoc Networks (VANETs) environment in general. But they make longer routes causing by surroundings or turn out routing failures in some cases when there are many traffic signals which generate empty streets temporary, or there is no merge roads after a road divide into two roads. When a node selects the next node simply using the distance to the destination node, the longer route is made by traditional greedy protocols in some cases and sometimes the route ends up routing failure. Most of traditional greedy protocols just take into account the distance to the destination to select a next node. Each node needs to consider not only the distance to the destination node but also the direction to the destination while routing a packet because of geographical environment. The proposed routing scheme considers both of the distance and the direction for forwarding packets to make a stable route. And the protocol can configure as the surrounding environment. We evaluate the performance of the protocol using two mobility models and network simulations. Most of network performances are improved rather than in compared with traditional greedy protocols.

A Simulation Model for Evaluating Demand Responsive Transit: Real-Time Shared-Taxi Application (수요대응형 교통수단 시뮬레이션 방안: Real-Time Shared-Taxi 적용예시)

  • Jung, Jae-Young
    • International Journal of Highway Engineering
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    • v.14 no.3
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    • pp.163-171
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    • 2012
  • Demand Responsive Transit (DRT) services are becoming necessary as part of not only alternative transportation means for elderly and mobility impaired passengers, but also sustainable and flexible transportation options in urban area due to the development of communication technologies and Location Based Services (LBS). It is difficult to investigate the system performance regarding vehicle operational schemes and vehicle routing algorithms due to the lack of commercial software to support door-to-door vehicle simulation for larger area. This study proposes a simulation framework to evaluate innovative and flexible transit systems focusing on various vehicle routing algorithms, which describes data-type requirements for simulating door-to-door service on demand. A simulation framework is applied to compare two vehicle dispatch algorithms, Nearest Vehicle Dispatch (NVD) and Insertion Heuristic (IH) for real-time shared-taxi service in Seoul. System productivity and efficiency of the shared-taxi service are investigated, comparing to the conventional taxi system.

A Decentralized Coordination Algorithm for a Highly Dynamic Vehicle Routing Problem (동적 차량경로 문제에 대한 분산 알고리즘)

  • Okpoti, Evans Sowah;Jeong, In-Jae
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.42 no.4
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    • pp.116-125
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    • 2019
  • The Dynamic Vehicle Routing Problem (DVRP) involves a combinatorial optimization problem where new customer demands become known over time, and old routes must be reconfigured to generate new routes while executing the current solution. We consider the high level of dynamism problem. An application of highly dynamic DVRP is the ambulance service where a patient contacts the service center, followed by an evaluation of case severity, and a visit by a practitioner/ ambulance is scheduled accordingly. This paper considers a variant of the DVRP and proposes a decentralized algorithm in which collaborators (Depot and Vehicle), both have only partial information about the entire system. The DVRP is modeled as a periodic re optimization of VRP using the proposed decentralized algorithm where collaborators exchange local information to achieve the best global objective for the current state of the system. We assume the existence of a dispatcher e.g., headquarter of the company who can communicate to vehicles in order to gather information and assigns the new visits to them. The effectiveness of the proposed decentralized coordination algorithm is further evaluated using benchmark data given in literature. The results show that the proposed method performed better than the compared algorithms which utilize the centralized coordination in 12 out of 21 benchmark problems.

Agent-based control systemfordistributed control of AGVs (AGV의 분산제어를 위한 에이전트 기반의 제어시스템)

  • O, Seung-Jin;Jeong, Mu-Yeong
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2005.05a
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    • pp.1117-1123
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    • 2005
  • This paper deals with a new automated guided vehicle (AGV) control system for distributed control. Proposed AGV control system adapts the multi-agent technology. The system is composed of two types of controller: routing and order. The order controller is in charge of assignment of orders to AGVs. Through the bidding-based negotiation with routing controllers, the order controller assigns a new order to the proper AGV. The order controller announces order information to the routing controllers. Then the routing controllers generate a routing schedule for the order and make a bid according to the routing schedule. If the routing schedule conflicts with other AGV's one, the routing controller makes an alternative through negotiation with other routing controllers. The order controller finally evaluates bids and selects one. Each controller consists of a set of agents: negotiation agent, decision making agent and communication agent. We focus on the agent architecture and negotiation-based AGV scheduling algorithm. Proposed system is validated through an exemplary scenario.

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An Accelerated Genetic Algorithm for the Vehicle Routing Problem

  • Shin, Hae-Woong;Kang, Maing-Kyu
    • Journal of the Korean Operations Research and Management Science Society
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    • v.21 no.1
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    • pp.101-114
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    • 1996
  • This study suggests an accelerated genetic algorithm for the vehicle routing problem (AGAVRP). This algorithm treats both the single-visit and the multiple-visit models. AGAVRP is accelerated by the OR techniques at the various stages of the algorithm. In order to improve the convergence of AGAVRP, a robust set of parameters is determined by the experimental design approach. The relative performance of AGAVRP is comparable to the other known algorithms. The advantage of the proposed algorithm is flexibility and better convergence.

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A Heuristic for the Vehicle Routing Problem Allowing Multiple Visits (다회방문을 허용하는 차량경로문제의 발견적 해법)

  • 신해웅;강맹규
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.14 no.24
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    • pp.141-147
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    • 1991
  • This paper presents extended model for the vehicle routing problem, which allows multiple visits to a node by multiple vehicles. Multiple visits enables us split delivery. After formulating this multiple visits model mathematically, a two stage heuristic algorithm is developed by decomposition approach. This model consists of two sub-problem. The one is fixed cost transportation problem and the other is transportation problem.

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