Conference Agenda

La gestión portuaria eficiente es importante para el comercio marítimo. En la optimización de procesos logísticos, este estudio examina el uso de metodologías como la Simulación y la Programación lineal de enteros mixtos (MILP). Se destaca que estas metodologías son efectivas para identificar y corregir ineficiencias, lo que contribuye a la reducción de costos. Además, se analiza la importancia de optimizar los recursos, ya que esto maximiza la productividad. Esta revisión sistemática sugiere que un enfoque integral que combine tanto la metodología de Simulación como la MILP facilitaría la adaptabilidad de las cambiantes demandas del mercado. Por último, se destaca la importancia de explorar la combinación entre el análisis de datos y la inteligencia artificial para obtener mejores resultados y eficiencia operativa.

The increasing complexity of supply chains has driven the development of advanced technological solutions in logistics management. In this context, Artificial Intelligence (AI) has transformed the way logistics processes are optimized, allowing automation, massive data analysis, and improved decision-making. However, the implementation of AI faces challenges, such as methodological discrepancies, outdated studies, and barriers with training and technological integration. The main objective of this systematic review was to analyze the impact of AI on industrial logistics management. To do so, methods based on the PICOC strategy and the PRISMA methodology were used, selecting 137 relevant studies from SCOPUS, up to 2020 that analyzed best practices and the most effective approaches. The results revealed interesting findings in terms of productivity and competitiveness. However, areas for improvement and gaps in knowledge about some methods were also analyzed, highlighting the need to optimize the adoption of these technologies. The research provides valuable input in guiding decision makers, technology developers and academics, providing an overview of strategic tools that respond to the diverse needs in work areas in logistics management. In addition, it presents quantitative data, most used methods and key recommendations to maximize the benefits of AI in supply chains, ensuring a more efficient and sustainable implementation.

Based on the review of 40 scientific studies worldwide between 2015 and 2024, the main purpose is to analyze whether the use of electronic auctions allows automating logistics supply processes in organizations. This research uses an inductive approach from the particular to the general through a systematic review that includes analysis and synthesis of sources such as scientific articles, repositories and specialized journals, with the aim of identifying, consulting, extracting, collecting and integrating relevant data. Likewise, it concludes that, in logistics services, ICTs are effective in implementing electronic auctions, creating a transparent and auditable process in the management of purchases and supplies between suppliers and customers. Likewise, it allows the client company to have access to a greater number of suppliers and the supplier to increase its business opportunities. In turn, it was possible to identify that the automation obtained in the execution of electronic auctions speeds up the acquisition process by eliminating the need for prolonged negotiations and, consequently, making decisions in a more agile, transparent and efficient way with a reduction in costs that does not impact the quality of the product or service. The implementation of electronic auctions, beyond contributing to good logistics practices for continuous improvement, reveals valuable information on the performance of suppliers and market trends, facilitating the identification and selection of supplier companies for logistics and operations management.

In the electricity sector, efficiency in the management of transportation routes is essential to reduce costs and improve productivity. MABARA Contratistas Generales S.C.R.L., a provider of electrical services in the Lambayeque region of Peru, faces inefficiencies in route planning, which generates high operating costs and long travel times. The purpose of this study is to optimize the design of transportation routes to improve the company's operational efficiency. For this purpose, four optimization approaches were implemented and compared: sweep heuristics, savings heuristics, clustering heuristics and genetic algorithm, all programmed in Python. The evaluation was performed based on key indicators such as fuel costs, travel times, distance traveled, and operational efficiency. The results indicate that the savings heuristic is the most efficient method, achieving a 27.1% reduction in fuel costs, a 33% decrease in travel times and an 18.52% increase in operational efficiency. Therefore, it is concluded that the implementation of this method, together with personnel training and geographic information systems, significantly optimizes the company's logistics operations.

Urban mobility is crucial for community life in cities, as it facilitates movement between work, educational, recreational and commercial spaces; considering all the necessary journeys that people make using different means of transport. As the urban population grows, it becomes a challenge to adapt the development of the city to meet new mobility needs in a sustainable, inclusive and economical way. In this sense, one of the great goals is to balance these three pillars of sustainability, which requires a holistic approach in its study. This work aims to promote sustainable mobility through the development of methodologies for the collection of key data, such as vehicular flow and its characterization. The acquisition of these data allows the analysis of congestion, vehicle use trends, and estimation of pollutant emissions, facilitating the design of public policies and evidence-based decision-making. This study focuses on describing the methodology used in Bahía Blanca, Argentina, to perform manual vehicular flow counts and segmentation, by direct observation of videos at strategic points of the city. Ten-minute videos recorded during peak hours are used, and the data are extrapolated to one hour. The methodology has been applied in the micro and macro center of the city, as well as on university campuses, adapted to the objective of each study. This kind of research is pioneering in Bahía Blanca, with the purpose of assisting in the decision-making process of authorities. Finally, the methodology can be replicated in other cities, as long as it is adapted to the specific context.

Abstract – Wastewater treatment is essential to protect public health and water resources, particularly in urban areas where pollution and lack of sanitation services increase the risk of diseases such as cholera and hepatitis. This study evaluated the efficacy of the organic coagulants Moringa oleifera and Myrciaria dubia in the removal of E. coli from wastewater discharged at San Pedro Beach, Lurín, Lima. Untreated wastewater samples were collected, and doses of 1 g/L, 1.5 g/L, and 2 g/L of Moringa oleifera, as well as 0.7 mg/L, 0.8 mg/L, and 0.9 mg/L of Myrciaria dubia, were applied. The results showed an E. coli removal efficiency ranging from 97% to 100% with a 2 g/L dose of Moringa oleifera and from 99.8% to 99.9% with a 0.9 mg/L dose of Myrciaria dubia. This study underscores the importance of identifying and developing sustainable and effective alternatives for wastewater treatment in coastal areas, mitigating risks to public health and marine ecosystems.

In the context of higher education, computational thinking has been identified as a key skill for addressing complex problems across various disciplines. Therefore, this research aimed to evaluate the effectiveness of implementing a training program in visual programming with Scratch as a means to strengthen computational thinking in mechanical and electrical engineering students. The study was conducted at two higher education institutions: the Instituto Tecnológico Bolivariano de Tecnología (ITB) and the Universidad Bolivariana del Ecuador (UBE), involving 240 students from the mechanical and electrical engineering programs. The training program was developed following the ADDIE instructional model. The evaluation was conducted through detailed rubrics and satisfaction surveys, using platforms such as Moodle for implementation. The main results showed that 85% of the students developed functional projects integrating advanced computational thinking concepts, while 92% completed all proposed activities. Interdisciplinary projects, covering areas such as economics and physics, highlighted the applicability of programming in real-world contexts, fostering knowledge transfer. Scratch proved to be an effective tool for teaching programming and computational thinking at advanced levels, promoting both technical and creative skills. The implemented pedagogical strategies increased student motivation and engagement. The results suggest that the course could be replicated in other educational institutions.