A column generation approach for optimized routing and coordination of a UAV fleet

Zillies, Julia; Westphal, Stephan; Thakur, Dinesh; Kumar, Vinay; Pappas, George J.; Scheidt, David

doi:10.1109/ssrr.2016.7784326

Cited by 7 publications

(9 citation statements)

References 6 publications

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“…For UAS-based surveillance missions, the VRPs have been solved by using the column generation method [29,39]. The extreme point of the CPP problem represents a route that is used as a design variable, y k p , in the master problem.…”

Section: Column Generation Of the Rbecom For Cpp Problemsmentioning

confidence: 99%

Energy-Constrained Multi-UAV Coverage Path Planning for an Aerial Imagery Mission Using Column Generation

Choi

Briceño

Mavris

2019

J Intell Robot Syst

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This paper presents a new Coverage Path Planning (CPP) method for an aerial imaging mission with multiple Unmanned Aerial Vehicles (UAVs). In order to solve a CPP problem with multicopters, a typical mission profile can be defined with five mission segments: takeoff, cruise, hovering, turning, and landing. The traditional arc-based optimization approaches for the CPP problem cannot accurately estimate actual energy consumption to complete a given mission because they cannot account for turning phases in their model, which may cause non-feasible routes. To solve the limitation of the traditional approaches, this paper introduces a new route-based optimization model with column generation that can trace the amount of energy required for all different mission phases. This paper executes numerical simulations to demonstrate the effectiveness of the proposed method for both a single UAV and multiple UAV scenarios for CPP problems.

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Section: Column Generation Of the Rbecom For Cpp Problemsmentioning

confidence: 99%

Energy-Constrained Multi-UAV Coverage Path Planning for an Aerial Imagery Mission Using Column Generation

Choi

Briceño

Mavris

2019

J Intell Robot Syst

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“…(2017), Oruc and Kara (2018), and Zillies et al. (2016). Additionally, some authors just consider the possible application of their proposed model to these humanitarian scenarios, and adjust their proposed problem by not limiting their applicability in emergency response scenarios, but do not focus their research on this application, like the models designed by Dorling et al.…”

Section: Discussion Of Trends and Future Researchmentioning

confidence: 98%

“…The logistics applications that stand out from the reviewed papers are the ones for parcel delivery and for surveillance and information collection. Besides, this review also found different applications in humanitarian logistics to respond as fast as possible in emergency scenarios including natural disasters, human‐made disastrous incidents, or the delivery of medical supplies (Dorling et al., 2016; Zillies et al., 2016; Cannioto et al., 2017; Oruc and Kara, 2018; Chauhan et al., 2019). Furthermore, some publications also dealt with internal logistics processes of a company during the assembly of products (Olivares et al., 2015) or to gather information of air and soil for agricultural purposes (Tokekar et al., 2016).…”

Section: Classificationmentioning

confidence: 95%

Unmanned aerial vehicles/drones in vehicle routing problems: a literature review

Viloria

Solano-Charris

Muñoz-Villamizar

et al. 2020

Int Trans Operational Res

192

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During recent years, advances in drone technologies have made them applicable in various fields of industry, and their popularity continues to grow. In this paper, the academic contributions on drones routing problems are analyzed between 2005 and 2019 to identify the main characteristics of these types of problems, as well as the research trends and recent improvements. The literature is classified according to the objectives optimized, solution methods, applications, constraints, and whether they use a complementary vehicle or not. Finally, a discussion for trends and future research is presented.

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“…Jevtiü used the traveling salesman problem (TSP) to design a shortest path method for UAVs to achieve coordinated coverage of a designated area [9]. Zillies researched a path flow formulation and a column generation algorithm to realize the use of a set of homogeneous UAVs to serve a series of specified target locations that needed to fulfill certain requirements [10]. Bakhshipou viewed the UAV collaborative search and rescue problem as a simpler shortest path problem that does not require a return to the starting point [11].…”

Section: Models Of Multi-uav Collaborative Task Allocation For Search...mentioning

confidence: 99%

Collaborative Task Allocation and Optimization Solution for Unmanned Aerial Vehicles in Search and Rescue

Han,

Jiang,

Wang

et al. 2024

Drones

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Earthquakes pose significant risks to national stability, endangering lives and causing substantial economic damage. This study tackles the urgent need for efficient post-earthquake relief in search and rescue (SAR) scenarios by proposing a multi-UAV cooperative rescue task allocation model. With consideration the unique requirements of post-earthquake rescue missions, the model aims to minimize the number of UAVs deployed, reduce rescue costs, and shorten the duration of rescue operations. We propose an innovative hybrid algorithm combining particle swarm optimization (PSO) and grey wolf optimizer (GWO), called the PSOGWO algorithm, to achieve the objectives of the model. This algorithm is enhanced by various strategies, including interval transformation, nonlinear convergence factor, individual update strategy, and dynamic weighting rules. A practical case study illustrates the use of our model and algorithm in reality and validates its effectiveness by comparing it to PSO and GWO. Moreover, a sensitivity analysis on UAV capacity highlights its impact on the overall rescue time and cost. The research results contribute to the advancement of vehicle-routing problem (VRP) models and algorithms for post-earthquake relief in SAR. Furthermore, it provides optimized relief distribution strategies for rescue decision-makers, thereby improving the efficiency and effectiveness of SAR operations.

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A column generation approach for optimized routing and coordination of a UAV fleet

Cited by 7 publications

References 6 publications

Energy-Constrained Multi-UAV Coverage Path Planning for an Aerial Imagery Mission Using Column Generation

Energy-Constrained Multi-UAV Coverage Path Planning for an Aerial Imagery Mission Using Column Generation

Unmanned aerial vehicles/drones in vehicle routing problems: a literature review

Collaborative Task Allocation and Optimization Solution for Unmanned Aerial Vehicles in Search and Rescue

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