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 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

A two-phase approach for periodic home health care planning

International audienceIn this paper, we study the problem of periodic vehicle routing encountered in Home Health Care (HHC). The problem can be considered as a Periodic Vehicle Routing Problem with Time Windows (PVRPTW). It consists in establishing a planning of visits to patients over a given time horizon so as to satisfy the adherence to the care plan while optimizing the routes used in each time period. One two-stage mathematical formulation of this problem is proposed. We then propose a Tabu Search (TS) and a MIP-based Neighborhood Search method to compute the weekly and daily plan, respectively. These approaches are tested on large size instances

Periodic vehicle routing problem in a health unit

In logistics of home health care services in the Health Units, the managers and nurses need to carry out the schedule and the vehicles routes for the provision of care at the patients' homes. Currently, in Portugal, these services are increasingly used but the problem is still, usually, solved manually and without computational resources. The increased demand for home health care due to the boost of the elderly people number entails a high associated cost which, sometimes, does not guarantee the quality of the service. In this sense, the periodic vehicle routing problem is a generalization of the classical vehicle routing problem in which routes are determined for a time horizon of several days. In this work, it is provided a periodic vehicle routing problem applied in the Health Unit in Bragança. An integer linear programming formulation for the real database, allowed to solve the problem in an efficient and optimized way using the CPLEXR software.Programa Operacional Temático Factores de Competitividade(POCI-01-0145-FEDER-007043

A Periodic Location Routing Problem for Collaborative Recycling

Motivated by collaborative recycling efforts for non-profit agencies, we study a variant of the periodic location routing problem, in which one decides the set of open depots from the customer set, the capacity of open depots, and the visit frequency to nodes, in an effort to design networks for collaborative pickup activities. We formulate this problem, highlighting the challenges introduced by these decisions. We examine the relative dfficulty introduced with each decision through exact solutions and a heuristic approach which can incorporate extensions of model constraints and solve larger instances. The work is motivated by a project with a network of hunger relief agencies (e.g., food pantries, soup kitchens and shelters) focusing on collaborative approaches to address their cardboard recycling challenges collectively. We present a case study based on data from the network. In this novel setting, we evaluate collaboration in terms of participation levels and cost impact. These insights can be generalized to other networks of organizations that may consider pooling resources

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

Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposal

Purpose: Disposal of infectious waste remains one of the most serious problems in the social and environmental domains of almost every nation. Selection of new suitable locations and finding the optimal set of transport routes to transport infectious waste, namely location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Design/methodology/approach: Due to the complexity of this problem, location routing problem for a case study, forty hospitals and three candidate municipalities in sub-Northeastern Thailand, was divided into two phases. The first phase is to choose suitable municipalities using hybrid fuzzy goal programming model which hybridizes the fuzzy analytic hierarchy process and fuzzy goal programming. The second phase is to find the optimal routes for each selected municipality using hybrid genetic algorithm which hybridizes the genetic algorithm and local searches including 2-Opt-move, Insertion-move and ?-interchange-move. Findings: The results indicate that the hybrid fuzzy goal programming model can guide the selection of new suitable municipalities, and the hybrid genetic algorithm can provide the optimal routes for a fleet of vehicles effectively. Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.Peer Reviewe