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Drone-Truck Arc Routing Problems: Models and Algorithms.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Drone-Truck Arc Routing Problems: Models and Algorithms./
作者:	Alenany, Emad.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2022,
面頁冊數:	117 p.
附註:	Source: Dissertations Abstracts International, Volume: 84-08, Section: B.
Contained By:	Dissertations Abstracts International84-08B.
標題:	Engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30242198
ISBN:	9798368482255

Drone-Truck Arc Routing Problems: Models and Algorithms.
Alenany, Emad.

Drone-Truck Arc Routing Problems: Models and Algorithms. - Ann Arbor : ProQuest Dissertations & Theses, 2022 - 117 p.

Source: Dissertations Abstracts International, Volume: 84-08, Section: B.

Thesis (Ph.D.)--State University of New York at Binghamton, 2022.

This item must not be sold to any third party vendors.

The development of drones can enhance the effectiveness of logistics by utilizing drones to provide services. This is because drones are not required to follow the ground road network system and can avoid congested areas. However, drones are also characterized with shortcomings such as short battery life which hinders their use alone for routingservices. The use of a combined system of drone(s) and truck(s) can overcome these drone shortcomings. The modeling and optimization of the combined operation of a drone(s) and truck(s) for Arc Routing Problem (ARP) are considered in this dissertation, defined as Drone-Truck ARP (DT-ARP). First, a single-drone-single-truck case is considered. An IP model is developed based on the modeling concept called an operation. In addition, a heuristic solution approach is provided to the problem following the route-first, cluster-second approach. The heuristic is characterized with the use of multiple initial truck routes and the adoption of local search and Simulated Annealing (SA) for the selection of the initial truck solution. Next, a multiple-drone-multiple-truck ARP case is considered, where each truck is working as a mobile hub to support the drone operations and each truck holds only a single drone. The problem is labeled mDmTs-ARP. This system is first studied in this dissertation. The studied system requires simultaneous optimization of the truck routes along the ground network and the drones’ network of required edges/arcs. Thus, the studied problem integrates the traveling salesman problem (TSP) and the ARP. Due to the complex nature of the problem, a heuristic consisting of multiple phases is proposed. Starting with generating multiple giant drone routes each assuming infinite drone endurance. Then, partitioning the giant drone route into multiple drone routes by assuming a more practical drone endurance. Next, splitting each drone route into feasible subroutes by considering the actual drone endurance and the time relationships between each drone and its truck. Finally, the mDmTs-ARP is extended to allow each truck to hold more than a single drone. A proposed mathematical model is proposed building on the multiple single-truck single-drone routes resulting from themDmTs-ARP with a singledrone/truck solution where each drone subroute is defined by its launch and recovery nodes, and the drone subroute length. A MILP model is proposed by modeling the problem as an instance of the vehicle routing problem with backhauls (VRPB) . In addition, a proposed two-phase methodology is proposed based on the multiple strip packing problem to pack the set of drone subroutes to trucks, then schedule them to a set of trucks that work as transporters for drones who work as a set of parallel machines.

ISBN: 9798368482255Subjects--Topical Terms:

561152
Engineering.
Subjects--Index Terms:

Arc routing problem

Drone-Truck Arc Routing Problems: Models and Algorithms.
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506 $a This item must not be sold to any third party vendors.
506 $a This item is not available from ProQuest Dissertations & Theses.
520 $a The development of drones can enhance the effectiveness of logistics by utilizing drones to provide services. This is because drones are not required to follow the ground road network system and can avoid congested areas. However, drones are also characterized with shortcomings such as short battery life which hinders their use alone for routingservices. The use of a combined system of drone(s) and truck(s) can overcome these drone shortcomings. The modeling and optimization of the combined operation of a drone(s) and truck(s) for Arc Routing Problem (ARP) are considered in this dissertation, defined as Drone-Truck ARP (DT-ARP). First, a single-drone-single-truck case is considered. An IP model is developed based on the modeling concept called an operation. In addition, a heuristic solution approach is provided to the problem following the route-first, cluster-second approach. The heuristic is characterized with the use of multiple initial truck routes and the adoption of local search and Simulated Annealing (SA) for the selection of the initial truck solution. Next, a multiple-drone-multiple-truck ARP case is considered, where each truck is working as a mobile hub to support the drone operations and each truck holds only a single drone. The problem is labeled mDmTs-ARP. This system is first studied in this dissertation. The studied system requires simultaneous optimization of the truck routes along the ground network and the drones’ network of required edges/arcs. Thus, the studied problem integrates the traveling salesman problem (TSP) and the ARP. Due to the complex nature of the problem, a heuristic consisting of multiple phases is proposed. Starting with generating multiple giant drone routes each assuming infinite drone endurance. Then, partitioning the giant drone route into multiple drone routes by assuming a more practical drone endurance. Next, splitting each drone route into feasible subroutes by considering the actual drone endurance and the time relationships between each drone and its truck. Finally, the mDmTs-ARP is extended to allow each truck to hold more than a single drone. A proposed mathematical model is proposed building on the multiple single-truck single-drone routes resulting from themDmTs-ARP with a singledrone/truck solution where each drone subroute is defined by its launch and recovery nodes, and the drone subroute length. A MILP model is proposed by modeling the problem as an instance of the vehicle routing problem with backhauls (VRPB) . In addition, a proposed two-phase methodology is proposed based on the multiple strip packing problem to pack the set of drone subroutes to trucks, then schedule them to a set of trucks that work as transporters for drones who work as a set of parallel machines.
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653 $a Arc routing problem
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653 $a Heuristic
653 $a Optimization
653 $a VRPB
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