1. NL2OR: Solve Complex Operations Research Problems Using Natural Language Inputs
- Author
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Li, Junxuan, Wickman, Ryan, Bhatnagar, Sahil, Maity, Raj Kumar, and Mukherjee, Arko
- Subjects
Computer Science - Artificial Intelligence ,Computer Science - Human-Computer Interaction - Abstract
Operations research (OR) uses mathematical models to enhance decision-making, but developing these models requires expert knowledge and can be time-consuming. Automated mathematical programming (AMP) has emerged to simplify this process, but existing systems have limitations. This paper introduces a novel methodology that uses recent advances in Large Language Model (LLM) to create and edit OR solutions from non-expert user queries expressed using Natural Language. This reduces the need for domain expertise and the time to formulate a problem. The paper presents an end-to-end pipeline, named NL2OR, that generates solutions to OR problems from natural language input, and shares experimental results on several important OR problems.
- Published
- 2024