Models and algorithms for the Flying Sidekick Traveling Salesman Problem

Dell’Amico, Mauro; Montemanni, Roberto; Novellani, Stefano

doi:10.48550/arxiv.1910.02559

Cited by 2 publications

(5 citation statements)

References 27 publications

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“…Mainly, we replicate most of the four-index constraints and the objective function, in particular ( 1)-( 29) and ( 34)- (40). Along the lines of what was done in Dell'Amico et al [13], we introduce the crossing sortie variables: new binary variables z v i , one for each node i ∈ N and each drone v ∈ D that take value 1 if the drone v is available for launching at node i, 0 otherwise. To guarantee this, we introduce the following constraints:…”

Section: Crossing Sortie Variables Formulation With Four-index Variablesmentioning

confidence: 82%

“…They also propose a set of inequalities to be separated in a branch-and-cut fashion. The same authors propose improved formulations that could solve larger instances in [13], and a matheuristic for the same problem in [14].…”

Section: Single Truck and Dronementioning

confidence: 99%

“…The equality guarantees that the waiting times are included between the truck departure and arrival times at every node and thus that the objective function decomposition holds. If drone v ∈ D performs the sortie (i, j, k, v) ∈ F, then the arrival time in k should include the departure time in i, the traveling times 𝜏 D ij and 𝜏 D jk , and the rendezvous time: this is guaranteed by constraint (13). We recall that the launching time is not considered in the flying time and thus it must be considered before t vA i .…”

Section: Truck Timing and Drone Timingmentioning

confidence: 99%

“…This significant difference between the values in the optimal solutions of the original model and those of the case with scheduling strongly justifies our interest in the scheduling component. FIGURE 13 Sequence of operations of two drones and the truck that can occur at a certain node in the case in which drones are allowed to wait on the ground…”

Section: Scheduling Versus No Schedulingmentioning

confidence: 99%

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Modeling the flying sidekick traveling salesman problem with multiple drones

2021

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This article considers a version of the flying sidekick traveling salesman problem in which parcels are delivered to customers by either a truck or a set of identical flying drones. The flights of the drones are limited by the battery endurance and each flight is made of a launch, a service to a customer, and a return: launch and return must happen when the truck is stationary. These operations require time and when multiple drones are launched and/or collected at the same node, their order becomes relevant. The proposed model takes into account the order of these operations as a scheduling problem, because ignoring it could lead to infeasible solutions in the reality due to the possible exceeding of the drones endurance. We propose a set of novel formulations for the problem that can improve the size of the largest instances solved in the literature. We provide a comparison among the formulations, between the multiple drones solutions and the single drone ones, and among different variants of the model.

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Section: Crossing Sortie Variables Formulation With Four-index Variablesmentioning

confidence: 82%

Section: Single Truck and Dronementioning

confidence: 99%

Section: Truck Timing and Drone Timingmentioning

confidence: 99%

Section: Scheduling Versus No Schedulingmentioning

confidence: 99%

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Modeling the flying sidekick traveling salesman problem with multiple drones

2021

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“…Reference [15] proposed a matheuristic based on a new formulation for the FSTSP model. Computational experiments showed that the approach could find good solutions when compared to other algorithms.…”

Section: Literature Reviewmentioning

confidence: 99%

A New Truck-Drone Routing Problem for Parcel Delivery Services Aided by Parking Lots

2021

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Collaborative routing aided by drones in last-mile delivery (LMD) has been an extensively studied topic in recent years. In this article, a new optimization problem for collaborative routing with a truck and a fleet of drones in LMD is introduced. The problem proposes a new strategy to coordinate a truck and a fleet of drones to serve a given set of customers. The plan is based on identifying the locations where the truck can park and where the drones fly to serve the customers. A procedure to locate these parking lots conveniently is given. For the transportation network, which includes these points, a mixed linear integer programming formulation is provided, which aims to minimize the makespan of serving all the customers. Computational experiments on a set of problem instances were conducted to analyze the model solutions' characteristics and find their computational limits. The experiments showed that the proposed model could significantly improve the results obtained when only the truck delivers. Additionally, we propose a GRASP metaheuristic to solve instances of greater size. Its computational performance was studied when applied to a set of instances with different characteristics. The paper discusses some insights obtained from the computational experimentation and presents future research directions. INDEX TERMSTraveling salesman problem with drones, last-mile delivery, drones routing, collaboration truck-drone, parking lots.

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Models and algorithms for the Flying Sidekick Traveling Salesman Problem

Cited by 2 publications

References 27 publications

Modeling the flying sidekick traveling salesman problem with multiple drones

Modeling the flying sidekick traveling salesman problem with multiple drones

A New Truck-Drone Routing Problem for Parcel Delivery Services Aided by Parking Lots

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