In 2020, the COVID-19 pandemic and its rapid spread shook health authorities worldwide at the regional and national levels. Healthcare systems had difficulty acquiring important supplies, such as face shields, which at that time were essential for healthcare staff. The need for this material increased with the spread of the pandemic. In most areas, warehouses did not have a sufficient stock of this product. This situation has occurred in the cities and provinces of Burgos (Spain). Volunteers (citizens and small companies) owning three-dimensional printers offered themselves to manufacture face shields. These volunteers are called “makers.” Similarly, different organizations (mainly Civil Protection) took charge of transport activities (delivery of material to the makers, collection of face shields, and delivery of the latter to hospitals and other entities). In this study, we were tasked with developing a system for planning and rationalizing these activities. The problems that were solved included a vehicle routing problem with different characteristics compared with other models in the literature. A previous work described this problem, and the heuristic method used for the planning. However, it is necessary to develop tools that are as efficient as possible for similar situations. In this study, we propose a mathematical formulation of the problem and a method based on the metaheuristic strategies variable neighborhood search and greedy randomize adaptative search procedure on a multistart framework. Different tests with real instances used during the period in which these activities were conducted show that the new method improves the results obtained by the previous method as well as the commercial software.
