ML-GA

Software · Wed Nov 08 00:00:00 EST 2017

OSTI ID:1489385

PAL, PINAKI ^[1]; MOIZ, AHMED ABDUL ^[2]; KODAVASAL, JANARDHAN; SOM, SIBENDU ^[2]

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1. UChicago Argonne
2. UCHICAGO ARGONNE, LLC

ML-GA is a software that can be used to expedite design optimization process combining machine learning and genetic algorithm approaches. It employs a machine learning (ML) model (any ML algorithm can be incorporated) to predict the quality (merit) of a design from the input parameters. Then, a stochastic global optimization genetic algorithm (GA) is used, with the machine learning model as the objective function, to optimize the input parameters based on the merit function. ML-GA is scalable to higher computational platforms like supercomputers and clusters enabling optimization to be performed in significantly short time frames (e.g., in a day).

• Short Name / Acronym: ML-GA; 005827MLTPL00
• Site Accession Number: ANL-SF-18-098
• Version: 00
• Programming Language(s): Medium: X; OS: R software/multiplatform
• Research Organization: Argonne National Laboratory (ANL), Argonne, IL (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V)
• Contributing Organization: UCHICAGO ARGONNE, LLC
• DOE Contract Number: AC02-06CH11357
• OSTI ID: 1489385
• Country of Origin: United States