JS Bermúdez, A del Rio Chanona, C Tsay - Computer Aided Chemical …, 2023 - Elsevier
… We consider inventorymanagement for a multi-echelon, multi-period supply chain: the goal is to maximize profits while satisfying constraints. We use InvManagement-v0 in the or-gym …
… and distributional ambiguity. Distributionally robust optimization has also been exploited for tactical healthcare supply chain management … the assumption of distributional ambiguity and …
R Burtea, C Tsay - Computers & Chemical Engineering, 2024 - Elsevier
… Reinforcement learning (RL) is a promising solution for difficult decision-making problems, such as inventorymanagement in chemical supply chains. However, enabling RL to explicitly …
… This chapter begins with a review of inventorymanagement policies, focusing on … , inventory review frequency, and push versus pull strategies. It explores classic inventorymanagement …
H Park, DG Choi, D Min - International Journal of Production Economics, 2023 - Elsevier
… our inventorymanagement problem. Section 4 discusses the methodology of the proposed structured RL algorithm for inventorymanagement. … under this distributional assumption for …
… Second, we introduce GTDQN, a distributionalreinforcement … It outperforms other distributional reinforcement learning … Inventorymanagement considers a multitude of factors. One …
… of distributional RL algorithms [32]. Instead of formalizing the objective via expected performance, distributional RL … In this work, we utilize distributional RL to consider risk-sensitive …
… distributional information for all sources of uncertainty can lead to substantial cost reductions in inventorymanagement … that the importance of including distributional information tends to …
M Mousa, D van de Berg, N Kotecha… - Computers & Chemical …, 2024 - Elsevier
… Most solutions to the inventorymanagement problem assume a centralization of information … A decentralized solution to inventorymanagement using multi-agent reinforcement learning …