a b s t r a c tThis paper presents a novel optimization algorithm that consists of metaheuristic processes to solve the problem of the capillary distribution of goods in major urban areas taking into consideration the features encountered in real life: time windows, capacity constraints, compatibility between orders and vehicles, maximum number of orders per vehicle, orders that depend on the pickup and delivery and not returning to the depot. With the intention of reducing the wide variety of constraints and complexities, known as the Rich Vehicle Routing Problem, this algorithm proposes feasible alternatives in order to achieve the main objective of this research work: the reduction of costs by minimizing distances and reducing the number of vehicles used as long as the service quality to customers is optimum and a load balance among vehicles is maintained.

The aim of the paper is to model urban distribution vehicle routing problems by means of hubs in large cities. The idea behind the urban distribution center (DC) is to provide buffer points where cargo and packages which are to be delivered to shops and businesses can be stored beforehand. At these centers, there will be other kinds of routing problems corresponding to other fairly similar distribution problems. In this paper, a new vehicle routing model (based on the known Time-Dependent Vehicle Routing Problem with Time Windows, TDVRPTW) has been carried out and a change in the traditional approach is proposed, by adopting a system in which some customers are served by urban DCs while remaining customers are served by traditional routes. This study is also motivated by recent developments in real time traffic data acquisition systems, as well as national and international policies aimed at reducing concentrations of greenhouse gases emitted by traditional vans. By using k DCs, the whole problem is now composed of k+1 problems: one special VRPTW for each DC in addition to the main problem, in which some customers and k DC are serviced. The model has been tested by simulating one real case of pharmaceutical distribution within the city of Zaragoza.

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The purpose of this paper to present a cooperative scheduling algorithm for solving the Dynamic Pickup and Delivery Problem with Time Windows (DPDPTW). The idea behind cooperative waiting strategies is to calculate simultaneously the waiting times for all nodes in the solution. Classical non-cooperative scheduling algorithms perform the scheduling for each route independently of the scheduling of the other routes. We present the Cooperative Scheduling Problem (CSP) based on the elliptical areas generated by vehicles waiting at their nodes. The CSP is solved by means of a genetic algorithm and is evaluated by using a set of benchmarks based on real-life data found in the literature. Initially, two waiting strategies are presented: Wait-Early-Time scheduling and Balanced-Departure scheduling. Extensive empirical simulations have been carried out by analyzing the degree of dynamism and the average waiting time, a new concept defined to take into account the gap between the time windows of pickup and delivery nodes. Copyright

The purpose of this manuscript is to present the Smart Driving Service (SDS), a customized mobile application and a complex microservices framework that is intended for not only professional drivers but also for novel people that need help during the driving time in their long-distance journeys. The European regulation about driving times, breaks and rest periods for drivers engaged in the carriage of freight is implemented into the system. Additionally, it is necessary to have a feedback report to detect the behavior of the drivers and what to do differently to drive better. This issue is addressed by implementing a Route Performance Index (RPI) to measure the drivers' compliances. The proposed service has been running in a production stage for 6 months with a reduction of the consumption of 2 liters/100km. Having into account that the company runs more than 100M km per year, the savings in fuel is very relevant apart from the environment impact reduction.