AI RESEARCH
From Data to Action: Accelerating Refinery Optimization with AI
arXiv CS.LG
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ArXi:2605.15085v1 Announce Type: cross Nowadays refinery optimization utilizes sheer amounts of data, which can be handled with modern Linear Programming (LP) software, but the interpreting and applying the results remains challenging. Large petrochemical companies use massive models, with hundreds of thousands of input matrix elements. The LP solution is mathematically correct, but simplifications are made in the model, and data supply errors may occur. Therefore, further insight is needed to trust the results.