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GEKKO Optimization Suite Selected as a 2020 Best Paper

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The BYU Process Research and Intelligent Systems Modeling (PRISM) group was awarded the 2020 Best Paper from the journal Processes (Impact Factor 1.963). The paper was selected based on impact metrics including citations, views, and under the direction of the editorial board. The paper has been cited 36 times (according to Google Scholar) since it was published in 2018. The award highlights the contributions of the authors to the Processes open-access journal. Contributions were made by Logan Beal, R. Abraham Martin, and Daniel Hill with Dr. John Hedengren as the research advisor. The work is an outcome of the NSF project #1547110, EAGER: Cyber-Manufacturing with Multi-echelon Control and Scheduling. Dr. Logan Beal is currently working for ExxonMobil in Houston, Texas. Dr. Abe Martin is working on aerospace programs in China Lake, CA. Daniel Hill is a current PhD student working on a Hybrid Nuclear Energy Systems with Idaho National Labs and the Department of Energy. The Gekko software is a package for Python and is downloaded about 10,000 times per month according to pypi.org. The package is currently under development to improve machine learning with optimization methods: https://machinelearning.byu.edu