MORL/D, a decomposition-based multi-objective RL method, yields the most balanced Pareto-front approximations across three supply chain network complexities when compared with weighted-sum PPO and NSGA-II.
, author Salehi Esfandarani, M
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Reinforcement Learning for Multi-Objective Multi-Echelon Supply Chain Optimisation
MORL/D, a decomposition-based multi-objective RL method, yields the most balanced Pareto-front approximations across three supply chain network complexities when compared with weighted-sum PPO and NSGA-II.