Browsing by Author "Contreras, Juan Pablo"
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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.Item A horizontal collaborative approach for planning the wine grape harvesting(2022) Basso, Franco; Varas, Mauricio; Bosch, Paul; Contreras, Juan Pablo; Pezoa, RaúlHorizontal collaboration is a strategy that has increasingly been used for improving supply chain operations. In this paper, we analyze the benefits of using a collaborative approach when optimally planning the wine grape harvesting process. Particularly, we assess how labor and machinery collaborative planning impacts harvesting costs. We model cooperation among wineries as a coalitional game with transferable costs for which the characteristic function vector is computed by solving a new formulation for planning the wine grape harvesting. In order to obtain stable coalitions, we devise an optimization problem that incorporates both rationality and efficiency conditions and uses the Gini index as a fairness criterion. Focusing on an illustrative case, we develop several computational experiments that show the positive effect of collaboration in the harvesting process. Moreover, our computational results reveal that the results depend strongly on the fairness criteria used. The Gini index, for example, favors the formation of smaller coalitions compared to other fairness criteria such as entropy.Item A New Genetic Algorithm Encoding for Coalition Structure Generation Problems(2020) Contreras, Juan Pablo; Bosch, Paul; Varas, Mauricio; Basso, FrancoGenetic algorithms have proved to be a useful improvement heuristic for tackling several combinatorial problems, including the coalition structure generation problem. In this case, the focus lies on selecting the best partition from a discrete set. A relevant issue when designing a Genetic algorithm for coalition structure generation problems is to choose a proper genetic encoding that enables an efficient computational implementation. In this paper, we present a novel hybrid encoding, and we compare its performance against several genetic encoding proposed in the literature. We show that even in difficult instances of the coalition structure generation problem, the proposed approach is a competitive alternative to obtaining good quality solutions in reasonable computing times. Furthermore, we also show that the encoding relevance increases as the number of players increases.Item Comment on “An algorithm for moment-matching scenario generation with application to financial portfolio optimization"(2018) Contreras, Juan Pablo; Bosch, Paul; Herrera, MauricioA paper by Ponomareva, Roman, and Date proposed a new algorithm to generate scenarios and their probability weights matching exactly the given mean, the covariance matrix, the average of the marginal skewness, and the average of the marginal kurtosis of each individual component of a random vector. In this short communication, this algorithm is questioned by demonstrating that it could lead to spurious scenarios with negative probabilities. A necessary and sufficient condition for the appropriate choice of algorithm parameters is derived to correct this issue.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.