Abstract
Abstract The vehicle routing problem is one of the most studied NP-hard combinatorial problem. In the food sector, the complexity of the issue grows because of the presence of strict constraints. Taking into account the variability and the restrictions typical of the dairy sector, the aim of this paper is to provide a practical tool for solving the milk collection problem in real scenarios. A heuristic approach has been proposed to determine a feasible solution for a real-life problem, including capacity and time constraints. Two different applications of the Nearest Neighbor algorithm have been modelled and compared with the current system. Different tests have been implemented for evaluating the suitability of the outcomes. Results show that the greedy approach allows for involving less vehicles and reducing the travel time. Moreover, the tool has been proved to be flexible, able to solve routing problems with stochastic times and high supply variability.
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