Models and algorithms for the optimization of real-world routing and logistics problems

In the thesis we considered several real-world deterministic and stochastic problems that are included in the wide class of the VRPs, and we solved them by means of exact, heuristic, and metaheuristic methods. In particular, we treated three classes of real-world routing and logistics problem

Models and Algorihtm for the Optimization of Real-World Routing and Logistics Problems

Logistics involves planning, managing, and organizing the flows of goods from the point of origin to the point of destination in order to meet some requirements. Logistics and transportation aspects are very important and represent a relevant costs for producing and shipping companies, but also for public administration and private citizens. The optimization of resources and the improvement in the organization of operations is crucial for all branches of logistics, from the operation management to the transportation. As we will have the chance to see in this work, optimization techniques, models, and algorithms represent important methods to solve the always new and more complex problems arising in different segments of logistics. Many operation management and transportation problems are related to the optimization class of problems called Vehicle Routing Problems (VRPs). In this work, we consider several real-world deterministic and stochastic problems that are included in the wide class of the VRPs, and we solve them by means of exact and heuristic methods. We treat three classes of real-world routing and logistics problems. We deal with one of the most important tactical problems that arises in the managing of the bike sharing systems, that is the Bike sharing Rebalancing Problem (BRP). We propose models and algorithms for real-world earthwork optimization problems. We describe the 3DP process and we highlight several optimization issues in 3DP. Among those, we define the problem related to the tool path definition in the 3DP process, the 3D Routing Problem (3DRP), which is a generalization of the arc routing problem. We present an ILP model and several heuristic algorithms to solve the 3DRP

A two-echelon facility location problem with stochastic demands for urban construction logistics: An application within the SUCCESS project

In this paper we present a two-echelon facility location problem with stochastic demands for the introduction of consolidation centers in the construction supply chain in urban areas. We describe the state of the art and propose a 2-stage model solved with L-shaped algorithms where several novel features are treated all together. The study is part of simulations performed during the European project SUCCESS (Sustainable Urban Consolidation CentrES for construction)

Algorithms based on Branch and Bound for the Flying Sidekick Traveling Salesman Problem

The use of drones in urban logistics is gaining more and more interest. In this paper we consider the flying sidekick traveling salesman problem, where some customers require a delivery and they can be served either by a truck or by a drone. The aim is minimizing the total time required to service all the customers. We present a branch and bound algorithm especially designed to efficiently target small instances up to 15 customers and a heuristic algorithm, using the branch and bound as a subroutine, to attack larger instances. Extensive experimental results suggest the effectiveness of the exact solver for small instances and shows that the heuristic is able to provide state-of-the-art results for medium/large instances

Benchmark instances and optimal solutions for the traveling salesman problem with drone

The use of drones in logistics is gaining more and more interest, and drones are becoming a more viable and common way of distributing parcels in an urban environment. As a consequence, there is a flourishing production of articles in the field of operational optimization of the combined use of trucks and drones for fulfilling customers requests. The aim is minimizing the total time required to service all the customers, since this has obvious economical impacts. However in the literature there is not yet a widely recognized basic model, and there are not well assessed sets of instances and optimal solutions that can be considered as a benchmark to prove the effectiveness of new solution methods. The aim of this paper is to fill this gap. On one side we will clearly describe some of the most common components of the truck/drone routing problems and we will define nine basic problem settings, by combining these components. On the other side we will consider some of the instances used by many researchers and we will provide optimal solutions for all the problem settings previously identified. Instances and detailed solutions are then organized into benchmarks made publicly available as validation tools for future research methods.Comment: 21 pages, reference to benchmar

Models and algorithms for the Flying Sidekick Traveling Salesman Problem

This paper presents a set of new formulations for the Flying Sidekick Traveling Salesman Problem, where a truck and a drone cooperate to delivery parcels to customers minimizing the completion time. The new formulations improve the results of the literature by solving to optimality several benchmark instances for which an optimal solution was previously unknown. A matheuristic algorithm, strongly based on the new models, is also discussed. Experimental results show that this method is able to provide good quality solutions in short time even for the larger instances, on which the mathematical models struggle to provide either good heuristic solution or strong lower bounds.Comment: arXiv admin note: text overlap with arXiv:1905.1346

A destroy and repair algorithm for the Bike sharing Rebalancing Problem

In this paper, we deal with the Bike sharing Rebalancing Problem (BRP), which is the problem of driving a fleet of capacitated vehicles to redistribute bicycles among the stations of a bike sharing system. We tackle the BRP with a destroy and repair metaheuristic algorithm, which makes use of a new effective constructive heuristic and of several local search procedures. The computational effort required for the neighborhood explorations is reduced by means of a set of techniques based on the properties of feasible BRP solutions. In addition, the algorithm is adapted to solve the one-commodity Pickup and Delivery Vehicle Routing Problem with maximum Duration (1-PDVRPD), which is the variant of the BRP in which a maximum duration is imposed on each route. Extensive computational results on instances from the literature and on newly-collected large-size real-world instances are provided. Our destroy and repair algorithm compares very well with respect to an exact branch-and-cut algorithm and a previous metaheuristic algorithm in the literature. It improves several best-known solutions, providing high quality results on both problem variants