• Title/Summary/Keyword: Multiple Pickup and Delivery

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Logistics Allocation and Monitoring System based on Map and GPS Information (Map과 GPS 기반의 혼적을 고려한 물류할당 및 모니터링 시스템)

  • Park, Chulsoon;Bajracharya, Larsson
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.41 no.4
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    • pp.138-145
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    • 2018
  • In the field of optimization, many studies have been performed on various types of Vehicle Routing Problem (VRP) for a long time. A variety of models have been derived to extend the basic VRP model, to consider multiple truck terminal, multiple pickup and delivery, and time windows characteristics. A lot of research has been performed to find better solutions in a reasonable time for these models with heuristic approaches. In this paper, by considering realtime traffic characteristics in Map Navigation environment, we proposed a method to manage realistic optimal path allocation for the logistics trucks and cargoes, which are dispersed, in order to realize the realistic cargo mixing allowance and time constraint enforcement which were required as the most important points for an online logistics brokerage service company. Then we developed a prototype system that can support above functionality together with delivery status monitoring on Map Navigation environment. First, through Map Navigation system, we derived information such as navigation-based travel time required for logistics allocation scheduling based on multiple terminal multiple pickup and delivery models with time constraints. Especially, the travel time can be actually obtained by using the Map Navigation system by reflecting the road situation and traffic. Second, we made a mathematical model for optimal path allocation using the derived information, and solved it using an optimization solver. Third, we constructed the prototype system to provide the proposed method together with realtime logistics monitoring by arranging the allocation results in the Map Navigation environment.

Research of the Delivery Autonomy and Vision-based Landing Algorithm for Last-Mile Service using a UAV (무인기를 이용한 Last-Mile 서비스를 위한 배송 자동화 및 영상기반 착륙 알고리즘 연구)

  • Hanseob Lee;Hoon Jung
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.46 no.2
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    • pp.160-167
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    • 2023
  • This study focuses on the development of a Last-Mile delivery service using unmanned vehicles to deliver goods directly to the end consumer utilizing drones to perform autonomous delivery missions and an image-based precision landing algorithm for handoff to a robot in an intermediate facility. As the logistics market continues to grow rapidly, parcel volumes increase exponentially each year. However, due to low delivery fees, the workload of delivery personnel is increasing, resulting in a decrease in the quality of delivery services. To address this issue, the research team conducted a study on a Last-Mile delivery service using unmanned vehicles and conducted research on the necessary technologies for drone-based goods transportation in this paper. The flight scenario begins with the drone carrying the goods from a pickup location to the rooftop of a building where the final delivery destination is located. There is a handoff facility on the rooftop of the building, and a marker on the roof must be accurately landed upon. The mission is complete once the goods are delivered and the drone returns to its original location. The research team developed a mission planning algorithm to perform the above scenario automatically and constructed an algorithm to recognize the marker through a camera sensor and achieve a precision landing. The performance of the developed system has been verified through multiple trial operations within ETRI.

An Online Personal Rapid Transit Dispatching Algorithm Based on Nearest Neighbor Dispatching Rule (최근린 배차 규칙 기반 온라인 Personal Rapid Transit 배차 알고리즘)

  • Han, Chung-Kyun;Kwon, Bo Bea;Kim, Baek-Hyun;Jeong, Rag-Gyo;Lee, Hoon;Ha, Byung-Hyun
    • Journal of the Korea Society for Simulation
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    • v.23 no.4
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    • pp.97-109
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    • 2014
  • Personal rapid transit (PRT) is a new transportation system, which is energy efficient and brings high quality of customer service. Customers arrive dynamically at stations and request transportation service. In this paper, we propose a new online PRT dispatching algorithm for pickup and delivery of customers. We adopt the nearest neighbor dispatching rule, which is known as performing well in general. We extend the rule with bipartite matching in order to deal with multiple vehicles and customers at the same time. We suggest a systematic way for selecting vehicles that will be considered to be dispatched, since the scope with which vehicles are selected may affect the system performance. We regard the empty travel distance of vehicles and the customer waiting time as the performance measures. By using simulation experiments, it has been examined that the scope of dispatching affects the system performance. The proposed algorithm has been validated by comparing with other dispatching rules for transportation services. We have shown that our algorithm is more suitable for PRT operating environment than other dispatching rules.

A Dispatching and Routing Algorithm for Personal Rapid Transit by Considering Congestion (정체를 고려한 Personal Rapid Transit 배차 및 경로 계획 알고리즘)

  • Han, Chung-Kyun;Kim, Baek-Hyun;Jeong, Rag-Gyo;Ha, Byung-Hyun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.64 no.11
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    • pp.1578-1586
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    • 2015
  • Personal rapid transit (PRT) is getting attention as a new form of transportation. It is energy efficient and provides the high level of passenger service. In this study, the dynamic PRT dispatching and routing problem is dealt with. Passengers request transportation service on a complex network, and an operating system monitors passenger arrivals and coordinates vehicles in real time. A new online dispatching and routing algorithm is proposed, which minimizes the total travel distance of vehicles and the waiting time of passengers. The algorithm dispatches vehicles by considering multiple vehicles' state and multiple passengers at the same time. In particular, finding the shortest-time path is attempted by taking into account the future congestion on lanes. Discrete-event simulation is employed to validate the performance of the proposed algorithm. The results show the algorithm in this study outperforms others.