Significantly simplifying the creation of optimization models for real-world business problems has long been a major goal in applying mathematical optimization more widely to important business and societal decisions. The recent capabilities of Large Language Models (LLMs) present a timely opportunity to achieve this goal. Therefore, we propose research at the intersection of LLMs and optimization to create a Decision Optimization CoPilot (DOCP) - an AI tool designed to assist any decision maker, interacting in natural language to grasp the business problem, subsequently formulating and solving the corresponding optimization model. This paper outlines our DOCP vision and identifies several fundamental requirements for its implementation. We describe the state of the art through a literature survey and experiments using ChatGPT. We show that a) LLMs already provide substantial novel capabilities relevant to a DOCP, and b) major research challenges remain to be addressed. We also propose possible research directions to overcome these gaps. We also see this work as a call to action to bring together the LLM and optimization communities to pursue our vision, thereby enabling much more widespread improved decision-making.

通过结合大型语言模型和优化技术，我们提出了一个名为Decision Optimization CoPilot（DOCP）的人工智能工具，它旨在帮助决策者使用自然语言理解业务问题，并随后构建并解决相应的优化模型，从而显著简化了实际业务问题的优化模型的创建，从而实现更普遍的、改善决策的目标。

从大型语言模型和优化到决策优化CoPilot：一份研究宣言