https://hdl.handle.net/10259/3832 2026-06-21T21:34:52Z 2026-06-21T21:34:52Z Galán Ordax, José Manuel Díaz de la Fuente, Silvia Ahedo García, Virginia Santos Martín, José Ignacio https://hdl.handle.net/10259/11846 2026-06-17T00:05:32Z 2026-03-01T00:00:00Z

Optimizing classroom assignments to minimize epidemiological risk: the sibling rewiring problem Galán Ordax, José Manuel; Díaz de la Fuente, Silvia; Ahedo García, Virginia; Santos Martín, José Ignacio In the context of infectious diseases, the assignment of students to classroom groups can significantly influence infection dynamics within school environments, particularly when sibling relationships introduce latent connections between otherwise unconnected groups. Traditional grouping methods and pandemic-era bubble strategies do not explicitly optimize student network structures or account for equity in exposure. This study introduces the Sibling Rewiring Problem, a novel multi-objective framework for student assignment that aims to maximize network fragmentation, reduce potential contagion pathways and minimize variance in group sizes and epidemiological exposure—thereby promoting fairness. We compared baseline, heuristic, and metaheuristic strategies in realistic school scenarios. A simple heuristic that assigns siblings to the same classroom line when feasible consistently achieves substantial network fragmentation with minimal impact on equity. Simulated Annealing further improved these results, particularly in complex configurations with densely connected sibling networks. Our findings suggest that family-aware classroom assignments can enhance epidemiological resilience while maintaining socially acceptable distributions. This approach provides a practical and scalable framework for integrating public health considerations into educational planning and may inform future decision-making in both emergency and routine contexts

2026-03-01T00:00:00Z Izquierdo, Segismundo S. Izquierdo Millán, Luis Rodrigo https://hdl.handle.net/10259/10864 2025-09-13T00:05:28Z 2025-10-01T00:00:00Z

Statistical inference in games: Stability of pure equilibria Izquierdo, Segismundo S.; Izquierdo Millán, Luis Rodrigo We consider sampling best response decision protocols with statistical inference in population games. Under these protocols, a revising agent observes the actions of k randomly sampled players in a population, estimates from the sample a probability distribution for the state of the population (using some inference method), and chooses a best response to the estimated distribution. We formulate deterministic approximation dynamics for these protocols. If the inference method is unbiased, strict Nash equilibria are rest points, but they may not be stable. We present tests for stability of pure equilibria under these dynamics. Focusing on maximum-likelihood estimation, we can define an index that measures the strength of each strict Nash equilibrium. In tacit coordination or weakest-link games, the stability of equilibria under sampling best response dynamics is consistent with experimental evidence, capturing the effect of strategic uncertainty and its sensitivity to the number of players and to the cost/benefit ratio.

2025-10-01T00:00:00Z Izquierdo, Segismundo S. Izquierdo Millán, Luis Rodrigo Hauert, Christoph https://hdl.handle.net/10259/10460 2025-05-14T00:05:15Z 2025-07-01T00:00:00Z

Positive and negative selective assortment Izquierdo, Segismundo S.; Izquierdo Millán, Luis Rodrigo; Hauert, Christoph In populations subject to evolutionary processes, the assortment of players with different genes or strategies can have a large impact on players’ payoffs and on the expected evolution of each strategy in the population. Here we consider assortment generated by a process of partner choice known as selective assortment. Under selective assortment, players looking for a mate can observe the strategies of a sample of potential mates or co-players, and select one of them to interact with. This selection mechanism can generate positive assortment (preference for players using the same strategy), or negative assortment (preference for players using a different strategy). We study the impact of selective assortment in the evolution and in the equilibria of a population, providing results for different games under different evolutionary dynamics (including the replicator dynamics).

2025-07-01T00:00:00Z Ahedo García, Virginia Santos Martín, José Ignacio Galán Ordax, José Manuel https://hdl.handle.net/10259/9520 2024-09-03T00:05:15Z 2024-07-01T00:00:00Z

Network-based quality index aggregation in the retail location problem. A supervised learning approach Ahedo García, Virginia; Santos Martín, José Ignacio; Galán Ordax, José Manuel In retailing, the location problem is a fundamental strategic aspect. It is usually formalized as a multi-criteria optimization problem to choose the most appropriate spot. A relevant element in the selection is the adequacy of the commercial ecosystem in the vicinity of the location. To account for this criterion, there are different primary indices based on networks that formalize the quality of the available options with regard to the surrounding ecosystem. Previous research suggests that aggregating the different indices using a classifier can improve the quality of these metrics. In this paper, we compare different classifiers to assess their performance in that respect. The analysis has been performed in a context of transfer knowledge and information fusion using data from all the cities in Castile and Leon, Spain. Our results show that the random forest and generalized linear models obtain results significantly superior to other alternatives.; El problema de la localización en el comercio minorista es un aspecto estratégico fundamental. Suele formalizarse como un problema de optimización multicriterio para elegir la ubicación más adecuada. Un elemento relevante en la selección es la adecuación del ecosistema comercial en las proximidades de la localización. Bajo este criterio, existen diferentes índices primarios basados en redes para formalizar la calidad de las opciones disponibles con respecto al ecosistema circundante. Investigaciones anteriores sugieren que la agregación de los distintos índices mediante un clasificador puede mejorar la calidad de estas métricas. En este artículo, comparamos distintos clasificadores para evaluar su rendimiento. El análisis se ha realizado en un contexto de transferencia de conocimiento y fusión de información utilizando datos de todas las ciudades de Castilla y León, España. Nuestros resultados muestran que el bosque aleatorio y los modelos lineales generalizados obtienen resultados significativamente superiores a otras alternativas.

2024-07-01T00:00:00Z