Ingeniería en Sistemas, Electrónica e Industrial
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Item Rutas de transporte para la distribución y entrega de productos de la empresa embutidos La Madrileña(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Carrera de Ingeniería Industrial, 2025-02) Molina Martínez Jomayra Elizabeth; Tigre Ortega Franklin GeovannyThe optimization of transportation routes is vitally important for organizations, since it allows them to improve the distribution of their products and reduce the associated logistics costs. The objective of this study was to optimize transportation routes for products distribution and delivery at Embutidos La Madrileña company. The applied methodology contemplates a diagnosis of the current situation in organization's transportation routes, as well as the identification of the costs associated to distribution of its products, together with an analysis of weighted factors for the selection of an optimization model, method and tool most applicable to the conditions for organization. Thus, a model based on the Travelling Salesman Problem (TSP) model was developed, using the Genetic Algorithm as a solution implemented through Microsoft Excel Solver. Results showed a representative reduction in traveled distances from 518.2 km to 267.2 km per week for mobile 1 and from 421.8 km to 254.6 km per week for mobile 2, which economically represents an estimated weekly saving in the total cost of transportation and distribution of $116.89 for mobile 1 and $93.38 for mobile 2. It is concluded that optimization techniques application are viable strategies to improve the product transportation and distribution operations.Item Programación de la producción en la empresa Textiles Pasteur mediante optimización matemática(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Carrera de Ingeniería Industrial, 2025-02) Segura Yánez Erick Alexander; Naranjo Chiriboga Israel ErnestoProduction scheduling is a key aspect for manufacturing companies to achieve their strategic objectives. However, many companies still rely on empirical methods that neither guarantee efficiency nor optimize processes. This project aims to use mathematical optimization to develop a model tailored to the specific production scheduling needs of Textiles Pasteur, offering a data-driven alternative to the company’s current method. Through a literature review, key model elements were identified, while field research provided insights into the company’s specific needs. The developed model follows a mixed-integer linear programming (MILP) approach aimed at minimizing the makespan. To solve the model, a genetic algorithm was implemented due to problems with nature and complexity. Several scenarios were tested to determine the order configuration that offered the best balance between makespan and model runtime, concluding that grouping by size and color was the most efficient strategy. The company provided a representative dataset of a typical production week, which was used to validate the model. Results demonstrated a makespan of 2641.77 minutes, equivalent to 5.5 working days of 8 hours each, compared to 5 simulated days by the dataset given. The model also improves the level of automation, detail and flexibility against changes. All these improvements highlight that the proposed model is a viable alternative capable of competing with the company’s current method