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The Reinforcement Learning (RL) is an efficient machine learning method for solving problems that an agent has no knowledge about the environment a priori. Improving efficiency of decision-making practices in a supply chain is a major competitive domain in today's uncertain business environments. The bullwhip effect is an important phenomenon in the supply chain, in which the order variability increases...
Coordination in the Supply Chain Management (SCM) plays a major role in competitive advantages in today's uncertain business environments. There is strong evidence of success in the supply chain performance in cases with high coordination among echelons. The bullwhip effect is an important phenomenon of amplification of demand in supply chain. By eliminating the bullwhip effect, it is possible to...
Improving decision-making practices in a supply chain is a major source of competitive advantage in today's uncertain business environments. There is strong evidence of success in the supply chain performance in cases with high coordination among echelons. The bullwhip effect is an important phenomenon in a supply chain, in which the order variability increases as orders move up in a supply chain...
In this paper, we first describe a multi-objective supply chain model and the optimization problem in Supply Chain Management (SCM), which includes measurements of cost, customer service fill rates and delivery flexibility. This model incorporates production and delivery. Then, we present an Ant Colony Optimization (ACO) application to the solution of some multi-objective optimization problems. We...
The reinforcement learning (RL) is an efficient and popular way for solving problems that an agent has no knowledge about the environment a priori, which owns two characteristics: trial-and-error and delayed rewards. An RL agent must derive an optimal policy by directly interacting with the environment and getting the information about the environment. Supply chain management (SCM) is a challenging...
Reinforcement learning (RL) is successfully applied to some dynamical and unpredictable domains. The Supply Chain Management (SCM) is NP-hard problem. Some proposed RL methods perform better than traditional tools for dynamic problem solving in SCM. It realizes on-line learning and performs efficiently in some applications, but RL agent reacts worse than some heuristic methods to sudden changes in...
Systematical study on real time coordination problems had been made, aiming at improving response ability to uncertainty for supply chain. Connotation and research content of supply chain real time coordination were determined with the study of coordination theory, emergency management and response decision technique. Organization structure, general procedure and critical technologies for supply chain...
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