The traveling salesman problem with release dates and drone resupply

Pina-Pardo, Juan C.; Silva, Daniel F.; Smith, Alice E.

doi:10.1016/j.cor.2020.105170

Cited by 51 publications

(16 citation statements)

References 18 publications

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“…Moreover, effective algorithms including quadratic heuristic clustering algorithm [22], local search algorithm [23], multi-child genetic algorithm [24], variable neighborhood search [25], and branch and cut algorithm [26,27] to solve the problem are designed to solve the problem. However, due to the specificality of constraints on the TSP in different research contexts, some researchers have introduced effective strategies such as discretization scheme and two-stage greedy initialization algorithm based on traditional algorithms to further improve search performance of these algorithms [28][29][30][31][32][33].…”

Section: Literature Reviewmentioning

confidence: 99%

Tourism route optimization based on improved knowledge ant colony algorithm

Luo

Wang

et al. 2022

Complex Intell. Syst.

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With the rapid development of tourism in the economy, popular demand for tourism also increases. Unreasonable distribution arises a series of problems such as reduction of tourist satisfaction and decrease of the income in tourist attractions. Based on consideration of tourism route planning, a mathematical model which takes the maximization of the overall satisfaction of all tourist groups as the objective function is established by taking the age and preferences of tourists, the upper limits of the tourist carrying capacity in various tourism routes, etc. as constraints. It aims to maximize income in tourist attractions while improving tourist satisfaction. Based on the tourist data of a travel agency, the statistical ideas of hierarchical clustering and random sampling are utilized to process the acquired data to obtain the simulation examples in the article. Aiming at this model, a knowledge-based hybrid ant colony algorithm is designed. On this basis, the mechanism of bacterial foraging algorithm is introduced. It improves the performance of the algorithm and avoids the generation of local optimal solution. At the same time, two knowledge models are in addition to improve the solution quality of the algorithm. Typical simulation indicates that the improved ant colony algorithm can find the optimal solution at a higher efficiency when solving the tourism route planning problem. The model can also satisfy the economic benefit of enterprises and achieves favorable path optimization effect under different optional routes, thus further verifying the effect liveness of the model.

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Section: Literature Reviewmentioning

confidence: 99%

Tourism route optimization based on improved knowledge ant colony algorithm

Luo

Wang

et al. 2022

Complex Intell. Syst.

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“…Pina-Pardo et al [100] propose the traveling salesman problem with release dates and drone resupply (TSPRD-DR), which aims to find the minimum time route for a single truck that is resupplied by a drone while enroute to fulfill customers' orders. The orders and their associated information are known at the beginning of the day, but they may not be ready to ship.…”

Section: ) Htdds With Drone Resupply Operationsmentioning

confidence: 99%

“…Dayarian et al [101] present the vehicle routing problem with drone resupply (VRPDR), which considers a fleet of vehicles and a fleet of drones assisting each other to perform home deliveries. Similar to Pina-Pardo et al [100], drones are used to resupply the truck, but unknown orders arrive dynamically throughout the day. While the truck is stationary, the resupply operation takes place, and two associated strategies are considered: restricted resupply and flexible resupply.…”

Section: ) Htdds With Drone Resupply Operationsmentioning

confidence: 99%

“…The truck can only be resupplied by the drone at the end of its delivery route with a restricted resupply, whereas the flexible resupply allows it to happen at some locations. Unlike TSPRD-DR [100], the VRPDR problem is not supported by an exact solution, and algorithms based on Nearest Insertion, Large Neighbourhood Search (LNS), and a greedy approach are incorporated.…”

Section: ) Htdds With Drone Resupply Operationsmentioning

confidence: 99%

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Hybrid Truck-Drone Delivery Systems: A Systematic Literature Review

Madani

Ndiaye

2022

IEEE Access

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Owing to the continued development of e-commerce, logisticians now have an outstanding obligation to tackle last-mile delivery challenges. A number of logistics providers have suggested the incorporation of drones with trucks to provide a more flexible delivery system. This paper analyzes the content of 95 publications related to hybrid truck-drone delivery systems (HTDDS) in the context of lastmile delivery. First, a brief overview of the potential implementation of drone delivery systems is presented, including their integration with other vehicles. The overview aims to demonstrate the operational characteristics of such systems and their implications. Then, the surveyed literature is classified based on vehicles roles, system configuration, problem formulation, and solution methods. In relation to this research, several key findings and potential research directions are discussed. Despite the high level of interest in HTDDS research, it is still in its early phases and requires improvements in various areas. The payload capacity, speed, range, and energy consumption are all factors that must be considered in the modeling of drone characteristics. Almost all studies identify customer requests before the delivery operation begins. However, customer demands for immediate delivery present an opportunity for real-time optimization to provide solutions for e-commerce activities. Environmental issues are developing, as the last-mile delivery problem is regarded as the most polluting portion of the supply chain. Thus, more consideration should be given to the environmental impact of HTDDS. Finally, research on drone routing related to air traffic management has received relatively little attention.INDEX TERMS Drones, hybrid truck-drone delivery systems, last-mile delivery, routing.

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“…Ha et al (2018) considered a new variant of the TSP-D in which the objective is to minimize operational costs that include the total transportation cost as well as the cost associated with the wasted time during which a vehicle has to wait for another [33]. Pina-Pardo et al ( 2021) introduced the so-called TSP with release dates and drone resupply [34]. This is a problem consisting of finding a minimum time route for a single truck that can receive newly available orders en route via a drone sent from the depot.…”

Section: Delivery By Dronementioning

confidence: 99%

On Optimizing a Multi-Mode Last-Mile Parcel Delivery System with Vans, Truck and Drone

et al. 2021

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This work focuses on the optimization of a last-mile delivery system with multiple transportation modes. In this scenario, parcels need to be delivered to each customer point. The major feature of the problem is the combination of a fleet of road vehicles (vans) with a drone. Each van visits a subset of demand nodes to be determined according to the route of the van. The drone serves the customers not served by vans. At the same time, considering the safety, policy and terrain as well as the need to replace the battery, the drone needs to be transported by truck to the identified station along with the parcel. From each such station, the drone serves a subset of customers according to a direct assignment pattern, i.e., every time the drone is launched, it serves one demand node and returns to the station to collect another parcel. Similarly, the truck is used to transport the drone and cargo between stations. This is somewhat different from the research of other scholars. In terms of the joint distribution of the drone and road vehicle, most scholars will choose the combination of two transportation tools, while we use three. The drone and vans are responsible for distribution services, and the trucks are responsible for transporting the goods and drone to the station. The goal is to optimize the total delivery cost which includes the transportation costs for the vans and the delivery cost for the drone. A fixed cost is also considered for each drone parking site corresponding to the cost of positioning the drone and using the drone station. A discrete optimization model is presented for the problem in addition to a two-phase heuristic algorithm. The results of a series of computational tests performed to assess the applicability of the model and the efficiency of the heuristic are reported. The results obtained show that nearly 10% of the cost can be saved by combining the traditional delivery mode with the use of a drone and drone stations.

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The traveling salesman problem with release dates and drone resupply

Cited by 51 publications

References 18 publications

Tourism route optimization based on improved knowledge ant colony algorithm

Tourism route optimization based on improved knowledge ant colony algorithm

Hybrid Truck-Drone Delivery Systems: A Systematic Literature Review

On Optimizing a Multi-Mode Last-Mile Parcel Delivery System with Vans, Truck and Drone

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