Abstract Operations Research Modeling Using Natural Language Inputs

• URL: http://arxiv.org/abs/2408.07272v2
• Date: Tue, 28 Jan 2025 18:40:26 GMT
• Title: Abstract Operations Research Modeling Using Natural Language Inputs
• Authors: Junxuan Li, Ryan Wickman, Sahil Bhatnagar, Raj Kumar Maity, Arko Mukherjee,
• Abstract summary: Operations research (OR) uses mathematical models to enhance decision-making, but developing these models requires expert knowledge and can be time-consuming.<n>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.
• Score: 9.105616622623629
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• 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.

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