Collaborative Truck-Drone Routing for Contactless Parcel Delivery During the Epidemic

Wu, Guohua; Mao, Ni; Luo, Qizhang; Xu, Binjie; Shi, Jianmai; Suganthan, Ponnuthurai Nagaratnam

doi:10.1109/tits.2022.3181282

Cited by 39 publications

(18 citation statements)

References 46 publications

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“…The work in [ 15 ] investigates a collaborative truck-drone routing problem for contactless parcel delivery (CRP-TD) during the COVID-19 pandemic. It develops an improved variable neighborhood descent (IVND), which combines the metropolis acceptance criterion of simulated annealing and the tabu list of the tabu search algorithm to solve the formulated problem, which minimizes the delivery time and considers energy consumption of drones.…”

Section: Drone Routing Algorithmsmentioning

confidence: 99%

“… Taxonomy of algorithms for drone routing in drone-based delivery systems: A-Ptr-Net [ 6 ], JRCS [ 12 ], FSTSP-STT [ 41 ], RL-TDCD [ 42 ], CRP-TD [ 15 ], EHTDDP [ 16 ], ODCS [ 44 ], CBPTCS [ 11 ], DDC [ 17 ], CDNC [ 51 ], Covadel [ 56 ], PA-NOP [ 57 ], GaRuDa [ 58 ], DeliveryCoin [ 60 ]. …”

Section: Drone Routing Algorithmsmentioning

confidence: 99%

“…Collaboration between truck and drones is shown to be successful to address the flight range and payload limitation problem of drones [ 67 , 68 , 69 ]. In [ 15 ], the authors proposed a contactless collaborative truck-drone delivery to prevent the further spread of COVID-19 disease. They formulated a mixed-integer linear programming to minimize the delivery time while considering the energy consumption model of drones.…”

Section: Research and Development Challengesmentioning

confidence: 99%

“…The overall trajectory or route planning to visit the customers/delivery points or CSs are derived as different variants of the travelling salesman problem (TSP) [ 10 , 12 , 13 , 14 ]. Many mathematical models such as mixed integer linear programming (MILP) [ 12 ], heuristic method [ 15 , 16 ], and reinforcement learning [ 6 ] have been adopted to obtain a sub-optimal solution under different objectives considering several constrains. The main objective of trajectory planning in drone-based delivery systems is minimizing the average delivery time [ 11 ] and maximizing coverage area to serve maximum number of customers in a single charge [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Drone Routing for Drone-Based Delivery Systems: A Review of Trajectory Planning, Charging, and Security

Raivi

Huda

Arafat

et al. 2023

Sensors

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Recently, owing to the high mobility and low cost of drones, drone-based delivery systems have shown considerable potential for ensuring flexible and reliable parcel delivery. Several crucial design issues must be considered to design such systems, including route planning, payload weight consideration, distance measurement, and customer location. In this paper, we present a survey of emerging drone routing algorithms for drone-based delivery systems, emphasizing three major drone routing aspects: trajectory planning, charging, and security. We focus on practical design considerations to ensure efficient, flexible, and reliable parcel delivery. We first discuss the potential issues arising when designing such systems. Next, we present a novel taxonomy based on the above-mentioned three aspects. We extensively review each algorithm for drone routing in terms of key features and operational characteristics. Furthermore, we compare the algorithms in terms of their main idea, advantages, limitations, and performance aspects. Finally, we present open research challenges to motivate further research in this field. In particular, we focus on the major aspects that researchers and engineers need to consider in order to design effective and reliable drone routing algorithms for drone-based delivery systems.

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Section: Drone Routing Algorithmsmentioning

confidence: 99%

Section: Drone Routing Algorithmsmentioning

confidence: 99%

Section: Research and Development Challengesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Drone Routing for Drone-Based Delivery Systems: A Review of Trajectory Planning, Charging, and Security

Raivi

Huda

Arafat

et al. 2023

Sensors

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show abstract

“…Salama M et al [8] established a joint distribution path optimization model for trucks and drones, and proposed a heuristic algorithm based on unsupervised learning. Kang et al [9] developed an accurate algorithm using the Benders decomposition method to solve the problem; Wu et al [10] used a variable neighborhood descent algorithm for contactless package distribution in collaboration with trucks and drones. The experimental results showed that this algorithm has the advantage of fast problem solving speed;…”

Section: Introductionmentioning

confidence: 99%

Collaborative distribution path optimization for multi-vehicles and multi-drones in the cold chain

Yinhe,

Xianglong,

Yujiao

et al. 2024

Third International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2023)

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Aiming at the problems of large cost, serious energy consumption and low distribution efficiency in cold chain logistics distribution. In this paper, the cargo damage cost, distribution cost and distribution time of cold chain vehicles and drones are considered comprehensively, and the total transportation cost is minimized as the optimization target model. The model is solved by artificial bee colony and genetic algorithm. A sensitivity analysis is performed for the speed of cold chain vehicles and drones. The results show that the cost of cargo damage and the total distribution time will decrease with the increase of the speed of cold chain vehicles and drones, but the speed of cold chain vehicles affects the two to a lesser extent compared to the speed of drones. The conclusions can provide distribution programs for logistics companies as well as help the government in decision-making.

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Energy‐consumption model for rotary‐wing drones

Li,

Zhan,

Wang

2024

Journal of Field Robotics

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With technological advancement, the use of drones in delivery systems has become increasingly feasible. Many companies have developed rotary‐wing drone (RWD) technologies for parcel delivery. At present, the limited endurance is the main disadvantage of RWD delivery. The energy consumption of RWDs must be carefully managed, and it is necessary to develop an effective energy‐consumption model to support RWD flight planning. Because the interaction between the forces on the RWD and its flying environment is very complex, it is challenging to estimate accurately the RWD energy consumption. This study summarizes several energy‐consumption models proposed in the literature, then we develop an RWD energy‐consumption model (called the integrated model) based on analyzing the dynamic equilibrium of forces and power consumption in flight phases (including climb, descent, hover, and horizontal flight). Computational experiments involving several commercial RWDs indicate that the integrated model is more effective than several models in the literature. In the case where an RWD completed one flight segment, on average, 87.63% of the battery capacity was consumed in the horizontal flight phase. We also analyzed the effects of the total mass and horizontal airspeed on the RWD endurance and found that a larger mass corresponded to shorter endurance, and in the experimental range of the horizontal airspeed, a higher horizontal airspeed corresponded to longer endurance. Moreover, the total mass affected the RWD endurance more significantly than the horizontal airspeed.

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Collaborative Truck-Drone Routing for Contactless Parcel Delivery During the Epidemic

Cited by 39 publications

References 46 publications

Drone Routing for Drone-Based Delivery Systems: A Review of Trajectory Planning, Charging, and Security

Drone Routing for Drone-Based Delivery Systems: A Review of Trajectory Planning, Charging, and Security

Collaborative distribution path optimization for multi-vehicles and multi-drones in the cold chain

Energy‐consumption model for rotary‐wing drones

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