8 citations · 23 across the 7 of their papers we have counts for
7 papers
MORSE: Multi-Objective Reinforcement Learning via Strategy Evolution for Supply Chain Optimization
Niki Kotecha, Ehecatl Antonio del Rio Chanona
In supply chain management, decision-making often involves balancing multiple conflicting objectives, such as cost reduction, service level improvement, and environmental sustainab…
Reinforcement learning for efficient and robust multi-setpoint and multi-trajectory tracking in bioprocesses
Sebastián Espinel-Ríos, José L. Avalos, Ehecatl Antonio del Rio Chanona +1
Efficient and robust bioprocess control is essential for maximizing performance and adaptability in advanced biotechnological systems. In this work, we present a reinforcement-lear…
Enhancing reinforcement learning for population setpoint tracking in co-cultures
Sebastián Espinel-Ríos, Joyce Qiaoxi Mo, Dongda Zhang +2
Efficient multiple setpoint tracking can enable advanced biotechnological applications, such as maintaining desired population levels in co-cultures for optimal metabolic division…
Simplest Mechanism Builder Algorithm (SiMBA): An Automated Microkinetic Model Discovery Tool
Miguel Ángel de Carvalho Servia, King Kuok, Hii +3
Microkinetic models are key for evaluating industrial processes' efficiency and chemicals' environmental impact. Manual construction of these models is difficult and time-consuming…
Discovery of mixing characteristics for enhancing coiled reactor performance through a Bayesian Optimisation-CFD approach
Nausheen Basha, Thomas Savage, Jonathan McDonough +2
Processes involving the manufacture of fine/bulk chemicals, pharmaceuticals, biofuels, and waste treatment require plug flow characteristics to minimise their energy consumption an…
The Automated Discovery of Kinetic Rate Models -- Methodological Frameworks
Miguel Ángel de Carvalho Servia, Ilya Orson Sandoval, Klaus Hellgardt +4
The industrialization of catalytic processes requires reliable kinetic models for their design, optimization and control. Mechanistic models require significant domain knowledge, w…