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You are invited to attend the System Dynamics Seminar Series being held on Friday, September 24th from 1:00-2:pm EST via Zoom: https://mit.zoom.us/j/96764037673 (password: SDSSFA21). Our guest speaker will be James Paine
Abstract: Bullwhip is a classic, yet persisting, problem with reverberating consequences in inventory management. Research on bullwhip has consistently emphasized behavioral influences for this phenomenon and leveraged behavioral ordering models to suggest interventions. However more recent model-free approaches have also seen success. In this work, the author develops algorithmic approaches towards mitigating bullwhip using both behaviorally grounded model-based approaches alongside a model-free dual deep Q-network reinforcement learning approach. In addition to exploring the utility of this specific model-free architecture to multi-echelon supply chains with imperfect information sharing and information delays, the author directly compares the performance of these model-based and model-free approaches. In doing so, this work highlights both the insights gained from exploring model-based approaches in the context of prior behavioral operations management literature and emphasizes the complementary nature of model-based and model-free approaches in approaching behaviorally grounded supply chain management problems. This research is still in a work-in-progress state, and all comments and critiques are very welcome!
Brief Bio: James Paine is a fourth-year doctoral candidate at the Sloan School of Management at MIT, studying System Dynamics and its applications to product and service delivery systems. Prior to coming to the System Dynamics group, James gained experience in the nuclear, reverse logistics, and consumer apparel industries, as both an engineer and product lifecycle-focused marketer. Currently, James focuses on behavioral operations management questions, including human-algorithm interactions, supply chain research and analytics, and dynamic modeling of product and service delivery systems.
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