Exact and heuristic approaches to Truck–Drone Delivery Problems
Collaborative delivery employing drones in last-mile delivery has been an extensively studied topic in recent years. In this paper, it is studied Truck–Drone Delivery Problems (TDDPs) in which a traditional delivery truck is gathered with a drone to cut delivery times and costs. The vehicles work to...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-01-01
|
| Series: | EURO Journal on Transportation and Logistics |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S219243762200019X |
| _version_ | 1811202106270416896 |
|---|---|
| author | Júlia C. Freitas Puca Huachi V. Penna Túlio A.M. Toffolo |
| author_facet | Júlia C. Freitas Puca Huachi V. Penna Túlio A.M. Toffolo |
| author_sort | Júlia C. Freitas |
| collection | DOAJ |
| description | Collaborative delivery employing drones in last-mile delivery has been an extensively studied topic in recent years. In this paper, it is studied Truck–Drone Delivery Problems (TDDPs) in which a traditional delivery truck is gathered with a drone to cut delivery times and costs. The vehicles work together in a hybrid operation involving one drone launching from a larger vehicle that operates as a mobile depot and a recharging platform. The drone launches from the truck with a single package to deliver to a customer. Each drone must return to the truck to recharge batteries, pick up another package, and launch again to a new customer location. This work proposes a novel Mixed Integer Programming (MIP) formulation and a heuristic approach to address the problem. The proposed MIP formulation yields better linear relaxation bounds than previously proposed formulations for all instances, and was capable of optimally solving several unsolved instances from the literature. A hybrid heuristic based on the General Variable Neighborhood Search metaheuristic combining Tabu Search concepts is employed to obtain high-quality solutions for large-size instances. The efficiency of the algorithm was evaluated on 1415 benchmark instances from the literature, and over 80% of the best known solutions were improved. |
| first_indexed | 2024-04-12T02:34:33Z |
| format | Article |
| id | doaj.art-b4283846f1504b85a29128478a7198c3 |
| institution | Directory Open Access Journal |
| issn | 2192-4384 |
| language | English |
| last_indexed | 2024-04-12T02:34:33Z |
| publishDate | 2023-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | EURO Journal on Transportation and Logistics |
| spelling | doaj.art-b4283846f1504b85a29128478a7198c32022-12-22T03:51:38ZengElsevierEURO Journal on Transportation and Logistics2192-43842023-01-0112100094Exact and heuristic approaches to Truck–Drone Delivery ProblemsJúlia C. Freitas0Puca Huachi V. Penna1Túlio A.M. Toffolo2Corresponding author.; Federal University of Ouro Preto, Department of Computing, BrazilFederal University of Ouro Preto, Department of Computing, BrazilFederal University of Ouro Preto, Department of Computing, BrazilCollaborative delivery employing drones in last-mile delivery has been an extensively studied topic in recent years. In this paper, it is studied Truck–Drone Delivery Problems (TDDPs) in which a traditional delivery truck is gathered with a drone to cut delivery times and costs. The vehicles work together in a hybrid operation involving one drone launching from a larger vehicle that operates as a mobile depot and a recharging platform. The drone launches from the truck with a single package to deliver to a customer. Each drone must return to the truck to recharge batteries, pick up another package, and launch again to a new customer location. This work proposes a novel Mixed Integer Programming (MIP) formulation and a heuristic approach to address the problem. The proposed MIP formulation yields better linear relaxation bounds than previously proposed formulations for all instances, and was capable of optimally solving several unsolved instances from the literature. A hybrid heuristic based on the General Variable Neighborhood Search metaheuristic combining Tabu Search concepts is employed to obtain high-quality solutions for large-size instances. The efficiency of the algorithm was evaluated on 1415 benchmark instances from the literature, and over 80% of the best known solutions were improved.http://www.sciencedirect.com/science/article/pii/S219243762200019XUnmanned Aerial VehicleTraveling Salesman ProblemDrone deliveryMixed-integer ProgrammingGeneral Variable Neighborhood Search |
| spellingShingle | Júlia C. Freitas Puca Huachi V. Penna Túlio A.M. Toffolo Exact and heuristic approaches to Truck–Drone Delivery Problems EURO Journal on Transportation and Logistics Unmanned Aerial Vehicle Traveling Salesman Problem Drone delivery Mixed-integer Programming General Variable Neighborhood Search |
| title | Exact and heuristic approaches to Truck–Drone Delivery Problems |
| title_full | Exact and heuristic approaches to Truck–Drone Delivery Problems |
| title_fullStr | Exact and heuristic approaches to Truck–Drone Delivery Problems |
| title_full_unstemmed | Exact and heuristic approaches to Truck–Drone Delivery Problems |
| title_short | Exact and heuristic approaches to Truck–Drone Delivery Problems |
| title_sort | exact and heuristic approaches to truck drone delivery problems |
| topic | Unmanned Aerial Vehicle Traveling Salesman Problem Drone delivery Mixed-integer Programming General Variable Neighborhood Search |
| url | http://www.sciencedirect.com/science/article/pii/S219243762200019X |
| work_keys_str_mv | AT juliacfreitas exactandheuristicapproachestotruckdronedeliveryproblems AT pucahuachivpenna exactandheuristicapproachestotruckdronedeliveryproblems AT tulioamtoffolo exactandheuristicapproachestotruckdronedeliveryproblems |