Drone-assisted deliveries: new formulations for the flying sidekick traveling salesman problem

In this paper we consider a problem related to deliveries assisted by an unmanned aerial vehicle, so-called drone. In particular we consider the Flying Sidekick Traveling Salesman Problem, in which a truck and a drone cooperate to deliver parcels to customers minimizing the completion time. In the following we improve the formulation found in the related literature. We propose three-indexed and two-indexed formulations and a set of inequalities that can be implemented in a branch-and-cut fashion. The methods that we propose are able to find the optimal solution for most of the literature instances. Moreover, we consider two versions of the problem: one in which the drone is allowed to wait at the customers, as in the literature, and one in which waiting is allowed only in flying mode. The solving methodologies are adapted to both versions and a comparison between the two is provided

Exact models for the flying sidekick traveling salesman problem

This paper presents three enhanced formulations for the flying sidekick traveling salesman problem, where a truck and a drone cooperate to deliver parcels to customers minimizing the completion time. The drone can leave and must return to the truck after visiting one customer, performing flights not exceeding its battery endurance while the truck can serve other customers. The new formulations allow to decrease the number of “big-M” constraints with respect to literature models and improve previous results by solving to optimality several benchmark instances for which an optimal solution was previously unknown. This paper also shows how to modify the new models to include several variants of the problem from the literature

Matheuristic algorithms for the parallel drone scheduling traveling salesman problem

In a near future drones are likely to become a viable way of distributing parcels in a urban environment. In this paper we consider the parallel drone scheduling traveling salesman problem, where a set of customers requiring a delivery is split between a truck and a fleet of drones, with the aim of minimizing the total time required to service all the customers. We present a set of matheuristic methods for the problem. The new approaches are validated via an experimental campaign on two sets of benchmarks available in the literature. It is shown that the approaches we propose perform very well on small/medium size instances. Solving a mixed integer linear programming model to optimality leads to the first optimality proof for all the instances with 20 customers considered, while the heuristics are shown to be fast and effective on the same dataset. When considering larger instances with 48 to 229 customers, the results are competitive with state-of-the-art methods and lead to 28 new best known solutions out of the 90 instances considered

Experimental study of the porosity of loose stacks of stiff cylindrical fibres: Influence of the aspect ratio of fibres

PACS. 45.70.-n Granular systems - 46.65.+g Random phenomena and media - 61.43.Gt Powders, porous materials,

Drone-assisted deliveries: new formulations for the flying sidekick traveling salesman problem

In this paper we consider a problem related to deliveries assisted by an unmanned aerial vehicle, so-called drone. In particular we consider the Flying Sidekick Traveling Salesman Problem, in which a truck and a drone cooperate to deliver parcels to customers minimizing the completion time. In the following we improve the formulation found in the related literature. We propose three-indexed and two-indexed formulations and a set of inequalities that can be implemented in a branch-and-cut fashion. The methods that we propose are able to find the optimal solution for most of the literature instances. Moreover, we consider two versions of the problem: one in which the drone is allowed to wait at the customers, as in the literature, and one in which waiting is allowed only in flying mode. The solving methodologies are adapted to both versions and a comparison between the two is provided

A Decision Support System for Earthwork Activities in Construction Logistics

Making decisions in a complex system such as the construction of a highway is a hard task that involves a combinatorial set of possibilities, concerning thousands of interrelated activities and resources over several years. In this paper we describe a decision support system (DSS) developed to assist project managers in decision making for the construction of the Autostrada Pedemontana Lombarda highway, in Italy. The considered problem evaluates the earthwork activities in de- tail and defines the minimum cost earthwork plan satisfying all constraints. The proposed DSS involves the use of linear programming to solve the earthwork pro- blem in a two-phase approach: in the first phase, an aggregate model determines the feasibility of the overall project, whereas in the second phase, disaggregate models determine the actual flows of each material. The DSS gathers the needed informa- tion directly from the master plan commonly used by the company and provides as output a set of visual solutions. The solution are yielded in short times and can be run many times with different data sets supporting a fast evaluation of different decisions. The provided solutions are also optimized and could substitute the previ- ous manual results. The DSS has been proved to be very effective for assisting the project managers of the above highway construction and is currently in use in other project

Optimizing the Nozzle Path in the 3D Printing Process

In this paper, we define the 3D printing routing problem, the problem of finding the optimal path of the nozzle in a fused deposition modeling 3D printing system, so as to minimize the time required to create on object. We formally model the problem with an integer linear programming formulation and then solve it via heuristic algorithms. We test the algorithms on a set of large-size real-life instances, comparing them with one of the most widely used open source software for the problem. We show that large time reductions can be obtained. We finally propose a set of interesting directions for future research