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Abstract Operations Research Modeling Using Natural Language Inputs

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arxiv 2408.07272 v2 pith:LMF3Y2UW submitted 2024-08-14 cs.AI cs.HC

Abstract Operations Research Modeling Using Natural Language Inputs

Junxuan Li , Ryan Wickman , Sahil Bhatnagar , Raj Kumar Maity , Arko Mukherjee This is my paper
classification cs.AI cs.HC
keywords languagenaturalmathematicalmodelsoperationsproblemsresearchsolutions
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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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