Routing for unmanned aerial vehicles: Touring dimensional sets

Puerto, Justo; Valverde, Carlos

doi:10.1016/j.ejor.2021.06.061

Cited by 14 publications

(11 citation statements)

References 17 publications

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“…First, in logistics, constrained by load weights and endurance distances, drones generally coordinate with trucks or other kinds of motherships. Second, the drone routing problems are generally formatted as IP [27,28] and MILP [26,[29][30][31][32][33][34][35][36][37][38] models. Considering various performance metrics, e.g., cost, distance, energy consumption, and consumer satisfaction, the drone routing problems can be formulated and analyzed by multi-objective optimization models [39,40].…”

Section: Drone-based Routing Problemsmentioning

confidence: 99%

“…Fourth, the drone routing problems generally couple drones and other devices, e.g., trucks [26,31,[36][37][38][39][40][41][42] and motherships [33,34], which makes the models challenging in algorithm development. Various algorithms, including meta-and math-heuristics [29][30][31][32][33][34][35], have been studied considering the problem and model features.…”

Section: Drone-based Routing Problemsmentioning

confidence: 99%

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Drone-Based Emergent Distribution of Packages to an Island from a Land Base

Tian

et al. 2023

Drones

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An island logistics system is vulnerable in emergency conditions and even isolated from land logistics. Drone-based distribution is an emerging solution investigated in this study to transport packages from a land base to the islands. Considering the drone costs, drone landing platforms in islands, and incorporation into the island ground distribution system, this study categorizes the direct, point-to-point, and cyclic bi-stage distribution modes: in the direct mode, the packages are distributed from the drone base station to the customers directly by drones; in the point-to-point mode, the packages are transported to the drone landing platform and then distributed to the customers independently; in the cyclic mode, the packages are distributed from a drone landing platform by a closed route. The modes are formulated, and evaluation metrics and solution methods are developed. In the experiments based on an island case, the models and solution methods are demonstrated, compared, and analyzed. The cyclic bi-stage distribution mode can improve drone flying distance by 50%, and an iterative heuristic algorithm can further improve drone flying distance by 27.8%, and the ground costs by 3.16%, average for the settings of twenty to sixty customers and two to four drone landing platforms. Based on the modeling and experimental studies, managerial implications and possible extensions are discussed.

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Section: Drone-based Routing Problemsmentioning

confidence: 99%

Section: Drone-based Routing Problemsmentioning

confidence: 99%

Drone-Based Emergent Distribution of Packages to an Island from a Land Base

Tian

et al. 2023

Drones

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“…Assuming that the drone has enough endurance to visit every target, the basic idea of the algorithm is to associate each target to one operation by solving a crossing postman problem with neighbors (XPPN) (see Puerto and Valverde, 2021) for the targets including

orig

and

dest

. Recall that the XPPN consists in finding a minimum total route that visits all the neighborhoods and traverses some fractions of the polygonal chains considered in the problem.…”

Section: A Matheuristic For the Multitarget‐mdrpmentioning

confidence: 99%

An extended model of coordination of an all‐terrain vehicle and a multivisit drone

Amorosi

Puerto

Valverde

2022

Int Trans Operational Res

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In this paper, a model that combines the movement of a multivisit drone with a limited endurance and a base vehicle that can move freely in the continuous space is considered. The mothership is used to charge the battery of the drone, whereas the drone performs the task of visiting multiple targets of distinct shapes: points and polygonal chains. For polygonal chains, it is required to traverse a given fraction of its lengths that represent surveillance/inspection activities. The goal of the problem is to minimize the overall weighted distance traveled by both vehicles. A mixed integer second‐order cone program is developed and strengthened using valid inequalities and giving good bounds for the Big‐M constants that appear in the model. A refined matheuristic that provides reasonable solutions in short computing time is also established. The quality of the solutions provided by both approaches is compared and analyzed on an extensive battery of instances with different number and shapes of targets, which shows the usefulness of our approach and its applicability in different situations.

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“…Based on this method, they develop two approaches to solve the complete problem, a dynamic programming‐based exact algorithm and a heuristic to generate high‐quality tours. Puerto and Valverde [26] address the problem of designing routes for drones that must visit a number of geographical elements to deliver some good or service. They present two formulations that are tested on a set of instances with different shapes of elements, second order cone (SOC) representable and polyhedral neighborhoods and polygonal chains.…”

Section: Introductionmentioning

confidence: 99%

The multi‐purpose K‐drones general routing problem

et al. 2023

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In this article, we present and solve the multi‐purpose ‐drones general routing problem (MP ‐DGRP). In this optimization problem, a fleet of multi‐purpose drones, aerial vehicles that can both make deliveries and conduct sensing activities (e.g., imaging), have to jointly visit a set of nodes to make deliveries and map one or more continuous areas. This problem is motivated by global healthcare applications that deploy multipurpose drones that combine delivery trips with collection of aerial imaging data for use in emergency preparedness and resilience planning. The continuous areas that have to be mapped may correspond to terrain surfaces (e.g., flooded areas or regions with a disease outbreak) or to infrastructure networks to be inspected. The continuous areas can be modeled as a set of lines so that each area is completely serviced if all the lines covering it are traversed. Thus, given a set of nodes and a set of lines, the problem is to design drone routes of shortest total duration traversing the lines and visiting the nodes, while not exceeding the range limit (flight time) and capacity (loading) of the drones. Unlike ground vehicles in classical routing problems, drones can enter a line through any of its points, service only a part of that line and then exit through another of its points. The possibility of flying directly between any two points of the network offered by drones can lead to reduced costs, but it increases the difficulty of the problem. To deal with this problem, the lines are discretized, allowing drones to enter and exit each line only at a finite set of points, thus obtaining an instance of the ‐vehicles general routing problem (‐GRP). We present in this article an integer programming formulation for the ‐GRP and propose a matheuristic algorithm and a branch‐and‐cut procedure for its solution. Results are provided for problems with up to 20 deliveries and up to 28 continuous areas.

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Routing for unmanned aerial vehicles: Touring dimensional sets

Cited by 14 publications

References 17 publications

Drone-Based Emergent Distribution of Packages to an Island from a Land Base

Drone-Based Emergent Distribution of Packages to an Island from a Land Base

An extended model of coordination of an all‐terrain vehicle and a multivisit drone

The multi‐purpose K‐drones general routing problem

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