Add to ORKGDriven by the ability to perform sequential decision-making in complex dynamic situations, Reinforcement Learning (RL) has quickly become a promising avenue to solve inventory control (IC) problems. The objective of this paper is to provide a comprehensive overview of the IC problems that have been effectively solved due to the application of RL. Our contributions include providing the first systematic review in this field of interest and application. We also identify potential extensions and come up with four propositions that formulate a theoretical framework that may help develop RL algorithms to solve complex IC problems. We recommend specific future research directions and novel approaches in solving IC problems
As a significant part of a supply chain, inventory management can involve predicting purchases from ...
Abstract. The problem of production control in serial manufacturing lines that consist of a number o...
This work provides a Deep Reinforcement Learning approach to solving a periodic review inventory con...
Driven by the ability to perform sequential decision-making in complex dynamic situations, Reinforce...
Inventory management is a sequential decision problem that can be solved with reinforcement learning...
Deep reinforcement learning (DRL) has shown great potential for sequential decision-making, includin...
Deep reinforcement learning (DRL) has shown great potential for sequential decision-making, includin...
Deep reinforcement learning (DRL) has shown great potential for sequential decision-making, includin...
Problem definition: Is deep reinforcement learning (DRL) effective at solving inventory problems? Ac...
Supply chain management (SCM) is believed to be a key factor in delivering competitive advantages fo...
In this study, we deal with the inventory management system of perishable products under the random ...
The objective of this paper is to examine the use and applications of reinforcement learning (RL) te...
Part 3: Data MiningInternational audienceThe common belief is that using Reinforcement Learning meth...
We consider here a single-item lot sizing problem with fixed costs, lead time, and both backorders a...
Deep reinforcement learning (DRL) has shown great potential for sequential decision-making, includin...
As a significant part of a supply chain, inventory management can involve predicting purchases from ...
Abstract. The problem of production control in serial manufacturing lines that consist of a number o...
This work provides a Deep Reinforcement Learning approach to solving a periodic review inventory con...
Driven by the ability to perform sequential decision-making in complex dynamic situations, Reinforce...
Inventory management is a sequential decision problem that can be solved with reinforcement learning...
Deep reinforcement learning (DRL) has shown great potential for sequential decision-making, includin...
Deep reinforcement learning (DRL) has shown great potential for sequential decision-making, includin...
Deep reinforcement learning (DRL) has shown great potential for sequential decision-making, includin...
Problem definition: Is deep reinforcement learning (DRL) effective at solving inventory problems? Ac...
Supply chain management (SCM) is believed to be a key factor in delivering competitive advantages fo...
In this study, we deal with the inventory management system of perishable products under the random ...
The objective of this paper is to examine the use and applications of reinforcement learning (RL) te...
Part 3: Data MiningInternational audienceThe common belief is that using Reinforcement Learning meth...
We consider here a single-item lot sizing problem with fixed costs, lead time, and both backorders a...
Deep reinforcement learning (DRL) has shown great potential for sequential decision-making, includin...
As a significant part of a supply chain, inventory management can involve predicting purchases from ...
Abstract. The problem of production control in serial manufacturing lines that consist of a number o...
This work provides a Deep Reinforcement Learning approach to solving a periodic review inventory con...