Reinforcement Learning to Manage Energy Efficient Supply Chains

Abstract

Reinforcement getting to know (RL) has emerged as an ability method to deal with electricity green supply chains and improve the sustainability of operations. This paper critiques the software of RL in supply chain management, exploring the primary programs, methodologies, and approaches of incorporating RL in power structures. We overview recent advances in RL that would be implemented to supply chain power modeling, in addition to the benefits and demanding situations that can stand up from using RL for superior management of delivery chains. Further, we provide a conclusion on the blessings of RL as a tool for managing power green supply chains and advise capacity programs for research that explores how RL can be used to enhance the sustainability of operations.