An Integer Programming Model for the Capacitated Vehicle Routing Problem with Drones

Wikarek, Jarosław; Sitek, Paweł; Zawarczyński, Ł.

doi:10.1007/978-3-030-28377-3_42

Cited by 15 publications

(10 citation statements)

References 14 publications

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“…The optimization of aerial logistic systems has also become a relevant research topic, involving approaches aimed at optimizing the operations of autonomous drones operating delivery services from depots located in close proximity of the final destinations [21], as well as hybrid systems involving the employment of heterogenous vehicles. In particular, the drone-truck cooperative approach, is considered a very effective operational scheme, involving several configurations such as single van-single drone [12,[22][23][24][25], single vanmultiple drones [26][27][28][29][30], and Multiple van-multiple drones [31][32][33].…”

Section: Literature Reviewmentioning

confidence: 99%

Energy Consumption Model of Aerial Urban Logistic Infrastructures

et al. 2021

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In the last decade, logistic systems based on small aerial vehicles (drones) have become attractive for urban delivery operations as a sustainable alternative to ground vehicles because they are not affected by the congestion of the road network, thus allowing for faster and more reliable services. Aerial logistic systems, however, require a substantially different approach to operations management and need specifically designed supportive infrastructures. While the research on urban aerial delivery mostly focuses on the optimization vehicle operations, the appropriate design of supportive infrastructures is seldom considered. This paper focuses on the energy efficiency of aerial logistic systems, and proposes a new original methodology to obtain a realistic estimate of the overall energy consumed by a swarm of drones employed for urban delivery, taking into account the extension of the area served and its specific features. The methodology proposed offers relevant information for the decision problems related to the appropriate sizing of the infrastructures, the dimensioning of the swarm of drones and the capacity of the energy storage system. The paper also reports a comparison with ground vehicles in the same scenarios, showing the relevant tradeoffs. The results obtained demonstrate how an appropriate design of the supportive infrastructures for urban aerial logistics may significantly impact the overall efficiency of the delivery system.

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Section: Literature Reviewmentioning

confidence: 99%

Energy Consumption Model of Aerial Urban Logistic Infrastructures

et al. 2021

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“…The most important limitation is energy consumption, which can result in a relatively limited range of flight, which is a typical disadvantage of multirotor UAVs. This issue can be solved, for example, by UAV docking stations [30] or by custom planned routes [31]. The relatively small endurance of multirotor UAVs is caused mainly by one of their advantages, namely its compact size, and limits the applicability of UAV-based flying weather stations as well as strong winds that may result in the destruction of the UAVs.…”

Section: Related Workmentioning

confidence: 99%

Weather Sensing in an Urban Environment with the Use of a UAV and WebRTC-Based Platform: A Pilot Study

Chodorek

Yastrebov

2021

Sensors

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Thanks to IoT, Internet access, and low-cost sensors, it has become possible to increase the number of weather measuring points; hence, the density of the deployment of sources that provide weather data for the needs of large recipients, for example, weather web services or smart city management systems, has also increased. This paper presents a flying weather station that carries out measurements of two weather factors that are typically included in weather stations (ambient temperature and relative humidity), an often included weather factor (atmospheric pressure), and a rarely included one (ultraviolet index). In our solution, the measurements are supplemented with a visual observation of present weather phenomena. The flying weather station is built on a UAV and WebRTC-based universal platform proposed in our previous paper. The complete, fully operational flying weather station was evaluated in field studies. Experiments were conducted during a 6-month period on days having noticeably different weather conditions. Results show that weather data coming from the flying weather station were equal (with a good approximation) to weather data obtained from the reference weather station. When compared to the weather stations described in the literature (both stationary weather stations and mobile ones), the proposed solution achieved better accuracy than the other weather stations based on low-cost sensors.

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“…Tis means that the drone can either return to the depot after completing a delivery or directly move to another customer to pick up goods. Wikarek et al [5] also explored the capacitated vehicle routing problem with drones, which involves drones delivering packages to customers while also retrieving packages from them using multiple mobile depots to launch and retrieve drones. However, their study only used drones for pickup and delivery independently rather than in synchronous conjunction with trucks.…”

Section: Introductionmentioning

confidence: 99%

Multivisit Drone-Vehicle Routing Problem with Simultaneous Pickup and Delivery considering No-Fly Zones

Liu,

Han,

Zhang

et al. 2023

Discrete Dynamics in Nature and Society

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The employment of drones for the distribution of goods represents a significant avenue for addressing logistical challenges at the end of the supply chain. The truck-drone cooperative delivery model overcomes drone limitations such as limited capacity and endurance and has emerged as a crucial mode of drone participation in logistics delivery. This delivery model effectively reduces delivery costs and shortens delivery times. Herein, we examine a variant of the truck-drone routing problem, which encompasses the strategic deployment and routing of multiple fleets of trucks, each equipped with an auxiliary drone. The objective is to fulfill all the pickup and delivery demands of a designated customer base while minimizing the overall route cost. Within this problem domain, drones are authorized to serve multiple customers within their capacity and endurance limits, providing both pickup and delivery services during each trip. However, the utilization of drones for servicing all customers is impeded by the existence of no-fly zones that have been implemented in numerous cities worldwide. These prescribed no-fly zones cause significant challenges when attempting to optimize the routing of truck-drone operations. Thus, this study constructs a mixed integer linear programming (MILP) model for the path optimization problem of joint service of trucks and drones considering no-fly zones and simultaneous pickup and delivery. Given the intricacy of the MILP model, we propose a two-stage heuristic algorithm based on a simulated annealing approach, combined with strategies for rectifying infeasible solutions and expediting algorithmic processes. During the phase of computational experimentation, we explore the advantages derived from enabling drones to serve multiple customers and assess the effectiveness of the proposed model and two-stage heuristic algorithm. Finally, sensitivity analysis is conducted on two key parameters.

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An Integer Programming Model for the Capacitated Vehicle Routing Problem with Drones

Cited by 15 publications

References 14 publications

Energy Consumption Model of Aerial Urban Logistic Infrastructures

Energy Consumption Model of Aerial Urban Logistic Infrastructures

Weather Sensing in an Urban Environment with the Use of a UAV and WebRTC-Based Platform: A Pilot Study

Multivisit Drone-Vehicle Routing Problem with Simultaneous Pickup and Delivery considering No-Fly Zones

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