Large Language Models for Supply Chain Optimization

TL;DR

This paper introduces OptiGuide, a framework combining Large Language Models with optimization techniques to improve transparency and understanding of supply chain decisions, demonstrated on real-world Microsoft data.

Contribution

The paper presents a novel framework that integrates LLMs with optimization for supply chain insights without compromising data privacy.

Findings

Effective in explaining optimization outcomes in supply chains

Supports what-if scenario analysis for decision making

Develops a benchmark for evaluating LLM explanations

Abstract

Supply chain operations traditionally involve a variety of complex decision making problems. Over the last few decades, supply chains greatly benefited from advances in computation, which allowed the transition from manual processing to automation and cost-effective optimization. Nonetheless, business operators still need to spend substantial efforts in explaining and interpreting the optimization outcomes to stakeholders. Motivated by the recent advances in Large Language Models (LLMs), we study how this disruptive technology can help bridge the gap between supply chain automation and human comprehension and trust thereof. We design OptiGuide -- a framework that accepts as input queries in plain text, and outputs insights about the underlying optimization outcomes. Our framework does not forgo the state-of-the-art combinatorial optimization technology, but rather leverages it to quantitatively answer what-if scenarios (e.g., how would the cost change if we used supplier B instead of supplier A for a given demand?). Importantly, our design does not require sending proprietary data over to LLMs, which can be a privacy concern in some circumstances. We demonstrate the effectiveness of our framework on a real server placement scenario within Microsoft's cloud supply chain. Along the way, we develop a general evaluation benchmark, which can be used to evaluate the accuracy of the LLM output in other scenarios.