M&SOM Practice Platform

Using Optimization and LLMs to Enhance Cloud Supply Chain Operations

Abstract

The cloud computing industry amounts to hundreds of billions of dollars in market size. In this talk, we give an overview of the challenges in sustaining cost-effective operations for Microsoft's cloud business, ranging from handling supply chain dependencies to multi-dimensional resource management under demand uncertainty. We describe our optimization solution to the server fulfillment problem, which deals with reliably shipping servers from warehouses to datacenters. We then highlight how we have been using large language models (LLMs) to explain the outcomes of that solver to supply chain planners and improve productivity. We conclude by describing future research directions in cloud operations management, and, more broadly, in the intersection of AI and optimization as part of the OptiGuide project.

Presenters: Beibin Li, Konstantina Mellou, Jeevan Pathuri, Ishai Menache, Bo Zhang

Beibin Li is a Senior Research Engineer at Microsoft Research, focusing on artificial intelligence and large language models (LLMs). He has contributed to multiple projects in these areas, including OptiGuide (using LLM for supply chain management), Reflect-RL (a system that enhances long-term decision-making by fine-tuning LLMs with reinforcement learning), and a system to train small language models tailored for application interactions. Before joining Microsoft Research, Beibin completed his PhD at the Paul G. Allen School of Computer Science and Engineering at the University of Washington, specializing in data adaptation for neural networks.

Konstantina Mellou is a Principal Researcher in the Machine Learning and Optimization group at Microsoft Research Redmond. She received her PhD in operations research from MIT, and before that her degree in electrical and computer engineering from the National Technical University of Athens in Greece. Her research interests are in the area of optimization and data-driven decision making with applications in cloud computing, transportation, and logistics. At Microsoft Research, she has been working on designing large-scale optimization solutions for cloud systems and applications; part of this work has been deployed in Microsoft Azure and Dynamics 365.

Jeevan Pathuri is a General Manager and Partner Director of Engineering for Microsoft's Cloud Supply Chain, where he leads the development of large-scale distributed systems, machine learning, and AI platforms. Jeevan has over 20 years of experience in the software engineering industry with a background in computer science and engineering. He holds a MS in computer science from Rensselaer Polytechnic Institute and a BA in computer science from San Jose State University. Before joining Microsoft, Jeevan worked at Amazon, where he developed systems that form the backbone of Amazon's Worldwide Retail Businesses.

Ishai Menache received his PhD in electrical engineering from the Technion, Israel. Subsequently, he was a postdoctoral associate at the Laboratory for Information and Decision Systems in MIT. Ishai has been with Microsoft Research since 2011, where he is a Partner Researcher and manager of the Machine Learning and Optimization (MLO) group. Ishai's research focuses on designing large-scale optimization frameworks that leverage machine learning algorithms and generative AI.

Bo Zhang is a Principal Software Engineering Manager at Microsoft's Cloud Supply Chain. He joined Microsoft in 2015 and leads the development of Intelligent Fulfillment System for supply chain optimization. Before joining Microsoft, he worked at Amazon for development of Amazon's distributed commerce platform. Bo received his PhD in computer engineering from Virginia Tech, specializing in distributed systems and synchronization algorithms.

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