LATIDIA · Investigación

Marco de Gemelos Digitales Impulsados por IA para la Optimización de la Automatización de la Logística de Almacenes

arXiv: 2610.38101v1Tipo de anuncio: nuevo Resumen: En los últimos años, la optimización logística del almacén se ha centrado cada vez más en sistemas inteligentes basados en datos para mejorar la eficiencia operativa. Producción estática convencional

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arXiv:2610.38101v1 Announce Type: new Abstract: In recent years, warehouse logistics optimization has increasingly focused on intelligent, data-driven systems to enhance operational efficiency. Conventional static product placement strategies are being progressively replaced by dynamic slotting approaches that can adapt to real-time variations in warehouse conditions. In this work, we present a novel framework that employs a reinforcement learning agent integrated within a FlexSim-based Digital Twin environment for real-time product placement optimization. The proposed agent continuously learns from streaming operational data, enabling it to reduce picking time while improving overall system throughput. The simulation environment models a four-zone warehouse layout with forklift-based material handling and leverages the Asset Administration Shell framework to