Conference Agenda

The primary objective of this study is to determine the optimal collaborative replenishment size for a food product category consisting of 18 subcategories in a modern-channel supermarket chain with 14 points of sale. To achieve this, an annual planning horizon divided into 12 monthly periods was considered, employing the dynamic programming algorithm proposed by Harvey Wagner and Thomson Whitin. This algorithm was informed by demand forecasts generated through robust prediction methodologies (Holt-Winter, Prophet, Polynomial Regression, and Random Forest) and the cost structures established by the supermarket chain.

To assess the sensitivity of the model to variations in ordering, purchasing, and inventory holding costs, two additional scenarios were designed alongside the baseline scenario. The first scenario presents an adverse environment, with a sustained monthly increase of 10% in these costs throughout the entire planning horizon. The second scenario combines favorable and unfavorable conditions: during the first half of the planning period, a 5% reduction in each of these costs is applied, followed by a 5% increase in the second half.

The results showed that, in the first scenario, the total cost of the inventory policy increased by an average of 3.44% per period compared to the baseline scenario. In contrast, the second scenario revealed a decrease of 0.4% per period compared to the same reference point. These findings demonstrate the capacity of the Wagner-Whitin mathematical model based on dynamic programming, reinforced with robust forecasting methodologies, to anticipate changes in ordering, purchasing, and inventory holding costs, thereby optimizing decision-making in replenishment management.

The role of port terminals is fundamental to articulate economies, commerce, and the growth of communities. The synergy between port terminals, customs, port authorities, shipping lines, customs agents, freight forwarders, logistics operators, and importers or exporters, is the pillar of the basis of competitiveness in supply chains that energizes the market through the process of buying and selling between exporters and importers. We live in a scenario of an increasing volume of containerized cargo at the global and regional level, with about 80% of trade by sea. It is therefore necessary to generate strategies for the port under study to be sustainable and generate greater value in the articulation of supply chains. Therefore, this research aims to minimize the economic impact associated with the opportunity costs, operational costs of the receiving process, and costs of shipping containers to a port operator. The present research begins with improving the level of accuracy of the forecast of the mobilized volume of TEUs (Twenty-foot Equivalent Units), then an improvement in the processes was designed through the use of tools of the Lean philosophy and the leveling of loads through the implementation of S&OP (Sales & Operations Planning). The use of this methodology will allow to achieve of a cumulative incremental volume of 86,250 additional containers to the average capacity, with an additional economic income of 6.9 million dollars for the company in a three-year horizon.

Every year, traffic accidents are increasing worldwide. Particularly, in Chile, between 2010 and 2019, the increase of traffic accidents was 55.8%, in contrast to the sustainable development goals established by the United Nations. The objective of this study is to identify the critical areas of occurrence of road accidents and their attributes involving young drivers, both men and women, in the commune of Santiago, Chile. In addition, this study seeks to determine whether there are spatial patterns of these road accidents in the identified critical zones. First, a Kernel density estimation analysis was performed to identify areas with a high concentration of traffic accidents involving young drivers. Subsequently, a global spatial autocorrelation analysis was conducted using Moran’s I index in the most critical areas identified in the previous analysis. The results of this study divulge three important zones with high concentration of road accidents involving young male and female drivers in the commune of Santiago. In addition, road accidents involving male drivers present a higher concentration than those involving female drivers, both for their occurrence and their attributes. Finally, the spatial autocorrelation analysis does not reveal any spatial pattern at the global level. These results may help authorities in the decision making process to implement mitigation measures for reducing the occurrence of road accidents, particularly in the most critical areas.

The Human-in-the-Loop (HITL) approach describes human participation in various stages of artificial intelligence system development. This research identifies the methods employed by end users for verifying and validating knowledge generated by generative artificial intelligence (GAI). A systematic literature review was conducted following the PRISMA protocol to analyze the methods used for knowledge verification and validation in the context of the HITL approach. The search equation, developed using a generative AI tool, was applied to the Scopus database and the AI-powered search engine Undermind, retrieving a total of 95 documents. After applying inclusion and exclusion criteria, 19 articles were selected for analysis. The findings allowed for the categorization of the identified methods into two groups: those used in the design and implementation stages of GAI systems and those employed by end users. However, persistent challenges remain, particularly the lack of detailed specification and formalization of knowledge verification and validation methods at the end-user level, which impacts the accuracy of responses and the control of generated knowledge creativity. Future research should focus on specifying, testing, and formalizing these methods to optimize their application within the HITL framework. This study contributes to the field by providing a set of methods for verifying and validating knowledge generated by GAI, thereby improving response accuracy and control over creativity.