Matheuristic algorithms for the parallel drone scheduling traveling salesman problem
In a near future drones are likely to become a viable way of distributing parcels in a urban environment. In this paper we consider the parallel drone scheduling traveling salesman problem, where a set of customers requiring a delivery is split between a truck and a fleet of drones, with the aim of...
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| Vydané v: | Annals of operations research Ročník 289; číslo 2; s. 211 - 226 |
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| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
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New York
Springer US
01.06.2020
Springer Springer Nature B.V |
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| ISSN: | 0254-5330, 1572-9338 |
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| Abstract | In a near future drones are likely to become a viable way of distributing parcels in a urban environment. In this paper we consider the parallel drone scheduling traveling salesman problem, where a set of customers requiring a delivery is split between a truck and a fleet of drones, with the aim of minimizing the total time required to service all the customers. We present a set of matheuristic methods for the problem. The new approaches are validated via an experimental campaign on two sets of benchmarks available in the literature. It is shown that the approaches we propose perform very well on small/medium size instances. Solving a mixed integer linear programming model to optimality leads to the first optimality proof for all the instances with 20 customers considered, while the heuristics are shown to be fast and effective on the same dataset. When considering larger instances with 48 to 229 customers, the results are competitive with state-of-the-art methods and lead to 28 new best known solutions out of the 90 instances considered. |
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| AbstractList | In a near future drones are likely to become a viable way of distributing parcels in a urban environment. In this paper we consider the parallel drone scheduling traveling salesman problem, where a set of customers requiring a delivery is split between a truck and a fleet of drones, with the aim of minimizing the total time required to service all the customers. We present a set of matheuristic methods for the problem. The new approaches are validated via an experimental campaign on two sets of benchmarks available in the literature. It is shown that the approaches we propose perform very well on small/medium size instances. Solving a mixed integer linear programming model to optimality leads to the first optimality proof for all the instances with 20 customers considered, while the heuristics are shown to be fast and effective on the same dataset. When considering larger instances with 48 to 229 customers, the results are competitive with state-of-the-art methods and lead to 28 new best known solutions out of the 90 instances considered. |
| Audience | Academic |
| Author | Dell’Amico, Mauro Novellani, Stefano Montemanni, Roberto |
| Author_xml | – sequence: 1 givenname: Mauro surname: Dell’Amico fullname: Dell’Amico, Mauro organization: Department of Sciences and Methods for Engineering, University of Modena and Reggio Emilia – sequence: 2 givenname: Roberto surname: Montemanni fullname: Montemanni, Roberto email: roberto.montemanni@unimore.it organization: Department of Sciences and Methods for Engineering, University of Modena and Reggio Emilia – sequence: 3 givenname: Stefano surname: Novellani fullname: Novellani, Stefano organization: Department of Sciences and Methods for Engineering, University of Modena and Reggio Emilia |
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| Keywords | Drone-assisted deliveries Traveling salesman problem Mixed integer linear programming Heuristic algorithms Matheuristics |
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| SubjectTerms | Algorithms Analysis Business and Management Combinatorics Customers Distribution Distribution channels Drone aircraft Drone vehicles Heuristic programming Integer programming Linear programming Management Mixed integer Operations research Operations Research/Decision Theory Original Research Scheduling Scheduling (Management) Technology application Theory of Computation Traveling salesman problem Urban environments |
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| Title | Matheuristic algorithms for the parallel drone scheduling traveling salesman problem |
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