1 citations · 3 across the 4 of their papers we have counts for
4 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…
Leveraging Graph Neural Networks and Multi-Agent Reinforcement Learning for Inventory Control in Supply Chains
Niki Kotecha, Antonio del Rio Chanona
Inventory control in modern supply chains has attracted significant attention due to the increasing number of disruptive shocks and the challenges posed by complex dynamics, uncert…
Control-Informed Reinforcement Learning for Chemical Processes
Maximilian Bloor, Akhil Ahmed, Niki Kotecha +3
This work proposes a control-informed reinforcement learning (CIRL) framework that integrates proportional-integral-derivative (PID) control components into the architecture of dee…
An Analysis of Multi-Agent Reinforcement Learning for Decentralized Inventory Control Systems
Marwan Mousa, Damien van de Berg, Niki Kotecha +2
Most solutions to the inventory management problem assume a centralization of information that is incompatible with organisational constraints in real supply chain networks. The in…