Person: Varas, Mauricio
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Publication Optimizing the wine transportation process from bottling plants to ports(2023) Basso, Franco; Contreras, Juan Pablo; Pezoa, Raúl; Troncozo, Alejandro; Varas, MauricioThe wine industry is a highly competitive sector for which any efficiency improvement in the wine supply chain plays a critical role in maintaining or increasing profitability. Literature shows several successful applications of operational research tools at each stage of the wine production process. However, unlike other stages, the transportation and distribution phase has not been given the same attention in the specialized literature. To bridge this gap, this article proposes an integer linear programming model to jointly determine a plan for the bottling and transportation of products to ports in order to minimize inventory, freight, and delay costs. This model can be optimally solved in less than one day for small instances of up to 25 jobs. In practice, however, some industrial instances can easily exceed 200 jobs, which precludes the use of this model to support decision-making. To cope with this issue, we devise a two-stage procedure that generates good-quality solutions for industrial-size instances of this problem in reasonable computing times. Particularly, we show that the GAP of the proposed heuristic solution is relatively low for a wide range of instances. Finally, a case study is conducted on a medium-sized Chilean winery we worked with, where the planning generated by the proposed heuristic reduces the costs corresponding to the transportation stage by 45.3% in the best case, compared to the initial planning of the winery.Publication A home hospitalization assignment and routing problem with multiple time windows, mandatory returns and perishable biological samples: A Chilean case study(2024) Varas, Mauricio; Baesler, Felipe; Basso, Franco; Contreras, Juan Pablo; Pezoa, Raúl; Rojas-Goldsack, María FranciscaThe increase in life expectancy and formal care has fostered the demand for home care services, including home hospitalization. For this service, decision-makers must allocate the staff and route the visits as efficiently as possible. To tackle this problem, in this paper, we devise a new mixed-integer programming formulation that incorporates several industry-specific features, including matching patients to medical specialties and synchronized visits of multiple specialists. Moreover, the proposed formulation also includes three features that have not been tackled simultaneously in the previous literature: multiple time windows, mandatory lunch breaks at the hospital, and fast delivery of perishable biological samples. The proposed model can be reduced to a vehicle routing problem with multiple times windows, known as NP-hard. Therefore, for solving large instances, we design a heuristic procedure composed of a constructive heuristic coupled with an improvement heuristic, which builds on a local branching scheme. To test the applicability of our approach, we conduct a case study focusing on the actual operations of Hospital Padre Hurtado of Santiago, Chile. Our computational experiments show that the model provides fully implementable solutions. Moreover, the heuristic procedure provides high-quality routes (regarding quality and solution times), making it a promising alternative to experience-based scheduling methods and state-of-the-art solvers.