The flexible periodic vehicle routing problem: modeling alternatives and solution techniques

In this thesis the Flexible Periodic Vehicle Routing Problem is introduced and studied. In this problem a carrier must establish a distribution plan to serve a given set of customers over a planning horizon using a fleet of homogeneous capacitated vehicles. The total demand of each customer is known for the time horizon and it can be satisfied by visiting the customer in several time periods. There is, however, a limit on the maximum quantity that can be delivered at each visit. The aim is to minimize the total routing cost. This problem can be seen as a generalization of the Periodic Vehicle Routing Problem which, instead, has fixed service schedules and fixed delivered quantities per visit. On the other hand, the Flexible Periodic Routing Problem shares some characteristics with the Inventory Routing Problem in which inventory levels are considered at each time period, the delivery of product is a decision of the problem and, typically, an inventory cost is involved in the objective function. The relation among these periodic routing problems is discussed and a worst-case analysis, which shows the advantages of the studied problem with respect to the problems with periodicity mentioned above, is presented. Furthermore, alternative mixed-integer programming formulations are described and computationally tested. Given the difficulty to optimally solve the studied problem for small size instances, a matheuristic is developed, which is able to solve large size instances efficiently. Extensive computational experiments illustrate the characteristics of the solutions of the problem and show that, also in practice, allowing flexible policies may produce substantial savings in the routing costs in comparison with both the Periodic Vehicle Routing Problem and the Inventory Routing Problem.: En esta tesis se presenta y estudia el Problema de Ruteo de Vehículos Periódico Flexible. En este problema, un transportista debe establecer un plan de distribución para atender a un conjunto determinado de clientes durante un horizonte de planificación utilizando una flota de vehículos con capacidad homogénea. La demanda total de cada cliente es conocida por el horizonte temporal y se puede satisfacer visitando al cliente en varios períodos de tiempo. Sin embargo, hay un límite en la cantidad máxima que se puede entregar en cada visita. El objetivo es minimizar el costo total de ruteo. Este problema puede verse como una generalización del Problema clásico de Ruteo de Vehículos Periódico que, en cambio, tiene programas de servicio fijos y cantidades de entrega fijas por visita. Por otro lado, el Problema de Ruteo de Vehículos Periódico Flexible comparte algunas características con el Problema de Ruteo de Inventarios en el cual los niveles de inventario se consideran en cada período de tiempo, la entrega del producto es una variable de decisión y, típicamente, un costo de inventario está involucrado en la función objetivo. Se discute la relación entre estos problemas periódicos de rutas y se presenta un análisis del peor de los casos, que muestra las ventajas del problema estudiado con respecto a los problemas periódicos mencionados anteriormente. Además, las formulaciones alternativas de programación entera mixta se describen y se prueban computacionalmente. Dada la dificultad de resolver a optimalidad el problema estudiado para instancias de tamaño pequeño , se desarrolla una matheurística que puede resolver instancias de gran tamaño de manera eficiente. Una extensa experiencia computacional ilustra las características de las soluciones del problema y muestra que, también en la práctica, permitir políticas flexibles puede producir ahorros sustanciales en los costos de ruteo en comparación con el Problema de Ruteo de Vehículos Periódico y el Problema de Rutas de Inventario.Postprint (published version

On green routing and scheduling problem

The vehicle routing and scheduling problem has been studied with much interest within the last four decades. In this paper, some of the existing literature dealing with routing and scheduling problems with environmental issues is reviewed, and a description is provided of the problems that have been investigated and how they are treated using combinatorial optimization tools

Industrial and Tramp Ship Routing Problems: Closing the Gap for Real-Scale Instances

Recent studies in maritime logistics have introduced a general ship routing problem and a benchmark suite based on real shipping segments, considering pickups and deliveries, cargo selection, ship-dependent starting locations, travel times and costs, time windows, and incompatibility constraints, among other features. Together, these characteristics pose considerable challenges for exact and heuristic methods, and some cases with as few as 18 cargoes remain unsolved. To face this challenge, we propose an exact branch-and-price (B&P) algorithm and a hybrid metaheuristic. Our exact method generates elementary routes, but exploits decremental state-space relaxation to speed up column generation, heuristic strong branching, as well as advanced preprocessing and route enumeration techniques. Our metaheuristic is a sophisticated extension of the unified hybrid genetic search. It exploits a set-partitioning phase and uses problem-tailored variation operators to efficiently handle all the problem characteristics. As shown in our experimental analyses, the B&P optimally solves 239/240 existing instances within one hour. Scalability experiments on even larger problems demonstrate that it can optimally solve problems with around 60 ships and 200 cargoes (i.e., 400 pickup and delivery services) and find optimality gaps below 1.04% on the largest cases with up to 260 cargoes. The hybrid metaheuristic outperforms all previous heuristics and produces near-optimal solutions within minutes. These results are noteworthy, since these instances are comparable in size with the largest problems routinely solved by shipping companies

A satellite navigation system to improve the management of intermodal drayage

The intermodal transport chain can become more efficient by means of a good organization of the drayage movements. Drayage in intermodal container terminals involves the pick up or delivery of containers at customer locations, and the main objective is normally the assignment of transportation tasks to the different vehicles, often with the presence of time windows. The literature shows some works on centralised drayage management, but most of them consider the problem only from a static and deterministic perspective, whereas the work we present here incorporates the knowledge of the real-time position of the vehicles, which permanently enables the planner to reassign tasks in case the problem conditions change. This exact knowledge of position of the vehicles is possible thanks to a geographic positioning system by satellite (GPS, Galileo, Glonass), and the results show that this additional data can be used to dynamically improve the solution

A heuristic solution method for node routing based solid waste collection problems

This paper considers a real world waste collection problem in which glass, metal, plastics, or paper is brought to certain waste collection points by the citizens of a certain region. The collection of this waste from the collection points is therefore a node routing problem. The waste is delivered to special sites, so called intermediate facilities (IF), that are typically not identical with the vehicle depot. Since most waste collection points need not be visited every day, a planning period of several days has to be considered. In this context three related planning problems are considered. First, the periodic vehicle routing problem with intermediate facilities (PVRP-IF) is considered and an exact problem formulation is proposed. A set of benchmark instances is developed and an efficient hybrid solution method based on variable neighborhood search and dynamic programming is presented. Second, in a real world application the PVRP-IF is modified by permitting the return of partly loaded vehicles to the depots and by considering capacity limits at the IF. An average improvement of 25% in the routing cost is obtained compared to the current solution. Finally, a different but related problem, the so called multi-depot vehicle routing problem with inter-depot routes (MDVRPI) is considered. In this problem class just a single day is considered and the depots can act as an intermediate facility only at the end of a tour. For this problem several instances and benchmark solutions are available. It is shown that the algorithm outperforms all previously published metaheuristics for this problem class and finds the best solutions for all available benchmark instances

Benets of tight coupled architectures for the integration of GNSS receiver and Vanet transceiver

Vehicular adhoc networks (VANETs) are one emerging type of networks that will enable a broad range of applications such as public safety, traffic management, traveler information support and entertain ment. Whether wireless access may be asynchronous or synchronous (respectively as in the upcoming IEEE 8021.11p standard or in some alternative emerging solutions), a synchronization among nodes is required. Moreover, the information on position is needed to let vehicular services work and to correctly forward the messages. As a result, timing and positioning are a strong prerequisite of VANETs. Also the diffusion of enhanced GNSS Navigators paves the way to the integration between GNSS receivers and VANET transceiv ers. This position paper presents an analysis on potential benefits coming from a tightcoupling between the two: the dissertation is meant to show to what extent Intelligent Transportation System (ITS) services could benefit from the proposed architectur

A Combined Method for Capacitated Periodic Vehicle Routing Problem with Strict Time Windows Considering Pickup and Delivery

The paper develops a model for the optimal management of periodic deliveries of a given commodity with known capacity called Capacitated Periodic Vehicle Routing Problem (CPVRP). Due to the large number of customers, it is necessary to incorporate strict time windows, and pick-up and delivery in the periodic planning.. The goal is to schedule the deliveries according to feasible combinations of delivery days and to determine the the routing policies of the vehicles. The objective is to minimize the sum of the costs of all routes over the planning horizon. We model the problem as a large-scale linear mixed integer program and we propose a combined approach to solve the problem