A Multi-Trip Vehicle Routing Problem for Small Unmanned Aircraft Systems-Based Urban Delivery

Choi, Younghoon; Robertson, Bradford E.; Mavris, Dimitri N.

doi:10.2514/1.c035473

Cited by 12 publications

(4 citation statements)

References 43 publications

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“…7, where m 1 = h 3 /2f r and m 2 = d. It can be seen from Fig. 7 that there are eight entrances to the rectangular target, but the reconnaissance paths are of the same length and are calculated as shown in (2).…”

Section: ) Cuboid Target Representation and Scouted Strategymentioning

confidence: 99%

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Multi-UAV Reconnaissance Task Allocation in 3D Urban Environments

Tian,

Xu,

Luo

et al. 2024

IEEE Access

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This paper considers a reconnaissance task allocation problem for multiple unmanned aerial vehicles (UAVs) in 3D urban environments. In this paper, we present an extended heterogeneous targets reconnaissance task allocation model which introduced cuboid targets for 3D urban environment to improve the fidelity of the model. A reconnaissance method is designed for each type of target, and the mission is described as a heterogeneous target multi-traveling salesman problem model for solving complex optimization problems with multiple constraints.To address these complex optimization problems, multi-group symbiotic organisms search algorithms (MGSOS) are proposed, which maintain the diversity of species in the population through multi-group strategies and enhance information exchange between individuals in three stages. Real-number encoding is used to satisfy partial constraints and simplify the search space, improving the optimization efficiency of the solution. The simulation results show that the MGSOS algorithm can consider the characteristics of UAV sensor performance and heterogeneous targets. It outperforms the common symbiotic organisms search (SOS) algorithm in terms of the optimality of assignment results, and is suitable for larger scale urban reconnaissance task allocation problems.INDEX TERMS 3D urban environment, generalized multi-traveling salesman problem, np-hard problem, symbiotic organisms search, task allocation, unmanned aerial vehicle.

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Section: ) Cuboid Target Representation and Scouted Strategymentioning

confidence: 99%

“…The basic task allocation problem that aims to find the shortest flight path can be formulated as multi-traveling salesman problem (MTSP) [1] or a vehicle routing problem (VRP) [2] model for solution. It is also necessary to optimize UAV's locations or trajectories [3], [4], [5].…”

Section: Introductionmentioning

confidence: 99%

Multi-UAV Reconnaissance Task Allocation in 3D Urban Environments

Tian,

Xu,

Luo

et al. 2024

IEEE Access

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show abstract

“…The paper introduces a new class of arc routing problem called MD-RPP-RV in which the vehicles are rechargeable and reused to perform multiple trips from multiple depots that can end up at different depots. Although using rechargeable and reusable vehicles capable of multiple trips is explored in the literature from the perspective of node routing problems [34][35][36][37][38], and reusable vehicles in arc routing problems like multi-trip CARP [11,21], the idea of integrating rechargeability and reusability aspects of vehicles to solve multi-depot arc routing problems using multiple trips has not been looked at in the literature to the best of our knowledge.…”

Section: Introductionmentioning

confidence: 99%

Multi-Trip Algorithm for Multi-Depot Rural Postman Problem with Rechargeable Vehicles

Sathyamurthy

Herrmann

Azarm

2023

Preprint

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“…Small electric drones are recently attracting the research community interest thanks to their increasing use in several industrial applications. Equipped by different tools and sensors, they can perform variety of tasks such as inspection and monitoring [1], delivery [2], agriculture tasks [3], wireless coverage [4], and they had also been useful in COVID-19 pandemic handling, by means of social distancing monitoring [5], thermal imaging and sanitization [6]. Great progress is being made in military field performing intelligence, surveillance, and reconnaissance missions to avoid human losses in dangerous situations [7,8].…”

Section: Introductionmentioning

confidence: 99%