Towards Autonomous Supply Chains: Defining Characteristics, Conceptual Framework, and Autonomy Levels
Autonomous supply chains (ASCs) are self-governing supply chains built upon intelligence and automation, where key structural entities can make and enforce decisions with little or no human intervention.
Mitigating Transient Bullwhip Effects in Supply Chains with Imperfect Demand Forecasts
The core message of this paper is to characterize and compute the worst-case order fluctuation experienced by a supply chain vendor under bounded forecast errors and demand fluctuations, and to develop a forecast-driven affine control strategy that minimizes this transient Bullwhip measure.
Leveraging Intelligent Recommender Systems as a Reactive Measure to Enhance Supply Chain Resilience
A data-driven supply chain disruption response framework based on intelligent recommender system techniques can be implemented as an effective first-step measure to mitigate supply chain disruptions.
Efficient Online Learning for Stackelberg Pricing in a Newsvendor Supply Chain
The core message of this paper is to devise an efficient online learning algorithm for a Stackelberg pricing game between a supplier (leader) and a retailer (follower) in a Newsvendor supply chain setting, where the demand parameters are initially unknown.
Optimizing Inventory Placement for Downstream Online Matching Problem Analysis
The authors analyze the inventory placement problem for downstream online matching, showing that optimizing offline surrogates offers constant-factor guarantees. The approach involves randomized rounding and sample-average approximation.
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