The periodic vehicle routing problem: a case study.

This paper deals with a case study which is a variant of the Periodic Vehicle Routing Problem (PVRP). As in the traditional Vehicle Routing Problem (VRP), customer locations each with a certain daily demand are given, as well as a set of capacitated vehicles. In addition, the PVRP has a horizon, say T days, and there is a frequency for each customer stating how often within this T-day period this customer must be visited. A solution to the PVRP consists of T sets of routes that jointly satisfy the demand constraints and the frequency constraints. The objective is to minimize the sum of the costs of all routes over the planning horizon. We develop different algorithms solving the instances of the case studied. Using these algorithms we are able to realize considerable cost reductions compared to the current situation.Periodic vehicle routing; Case study;

The milk collection problem with time constraint: An optimization study integrating simulation

Transport management and vehicle routing problems play a strong role on a company's efficiency and competitiveness. In the food sector, the complexity of the problem grows because of strict constraints. This paper addresses the dairy transportation problem and in particular tries to optimize the milk collection process of a real company. A two-step approach has been proposed to test the current system and solve the routing problem. First, starting from the “As is” collection tours, a travel salesman problem has been modelled. Later, the Nearest Neighbor algorithm has been implemented in order to find a global optimal solution. Finally, a stochastic simulation model integrates the solutions of the previous step in order to test the feasibility of the outcomes, primarily in terms of their capability to meet the time constraints of the tours. Results show that the greedy approach allows less vehicles to be involved, with a good potential on annual cost saving. On the other hand, the simulation outcomes highlight a borderline case, which is not always in line with the time constraints of the problem

An Integer Optimization Model for the Time Windows Periodic Vehicle Routing Problem with Delivery, Fleet, and Driver Scheduling

The vehicle routing problem (VRP) is a well-known combinatorial optimization problem which describes a homogeneous set of vehicles and routes, in which each vehicle starts from a depot and traverses along a route in order to serve a set of customers with known geographical locations. If the delivery routes are constructed for period of time, the VRP is generalized as periodic VRP (PVRP). This paper develops a model for the optimal management of periodic deliveries of meals of a catering company. The PVRP incorporates time windows, deliveries, fleet and driver scheduling in the periodic planning.. The objective is to minimize the sum of the costs of travelling and elapsed time over the planning horizon. We model the problem as a linear mixed integer program and we propose a feasible neighbourhood direct search approach to solve the problem

Modelo de roteamento para coleta de leite cru utilizando algoritmos genéticos

The article examines the use of a metaheuristic method – genetic algorithms – for evaluating a model of routes for raw milk collection. A model was implemented based on real data, collected through fieldwork, following the method of the «traveling agent’s problem», using the toolbox of Matlab® genetic algorithm. The results show that the routes obtained with the implementation of the genetic algorithm are feasible in terms of time and visited nodes, demonstrating the potential of this tool. The costs obtained by this method differ from the current methods by about 3%, which is within the range reported in the literature.El artículo presenta la utilización de un método metaheurístico –algoritmos genéticos– para la evaluación de un modelo de rutas de recolección de leche cruda. Se implementó un modelo a partir de datos reales, recolectados por medio de trabajo de campo, siguiendo el método del «problema del agente viajero», usando el toolbox de algoritmos genéticos de Matlab®. Los resultados evidencian que las rutas obtenidas con la implementación del algoritmo genético son viables en cuanto a tiempo y nodos visitados, lo que demuestra el potencial de esta herramienta. Los costos obtenidos por este método difieren de los actuales en alrededor de 3%, valor que está dentro de los márgenes reportados en la literatura.O artigo mostra o uso de um método meta heurístico - algoritmos genéticos - para avaliar um padrão de rotas de coleta de leite cru. Foi implementado um modelo baseado em dados reais, coletados por meio de trabalho de campo, seguindo o método do "Problema do Caixeiro Viajante", usando os algoritmos genéticos da caixa de ferramentas Matlab®. Os resultados mostram que as rotas obtidas com a implementação do algoritmo genético são viáveis em termos de tempo e de nós visitados, demonstrando assim o potencial desta ferramenta. Os custos obtidos por este método diferem dos atuais em aproximadamente 3%, o que está dentro do intervalo referido na literatura

A Hybrid approach for milk collection using trucks and trailers

acceptedVersio

An application of Special Ordered Sets to a periodic milk collection problem

We present an OR-based approach to support a milk collection problem in a special branch of dairy industry. The annual growth of the sector and the continuous imbalance between milk supply and demand, has urged the sector to look for a different approach to their daily milk collection problem. Specific details of the problem environment (i.e., the continuous production on supply level and the delivery conditions on demand level) gave rise to choose for a short- to medium-term planning approach. The proposed decision support system has to be considered as an efficient tool for generating stable milk collection plans which in turn also serves as an effective starting point for the vehicle routing problem. From a computational point of view it turned out that the application of Special Ordered Sets type 1 (SOS1) was very useful. Although it appears from literature that the computational advantage of SOS1 is restricted to supplementary model conditions, this study shows that these conditions are not necessarily neede