The Use of Simulation with Machine Learning and Optimization for a Digital Twin-A Case on Formula 1 DSS

Andrew Greasley; Gajanan Panchal; Avinash Samvedi

doi:10.1109/wsc57314.2022.10015299

The Use of Simulation with Machine Learning and Optimization for a Digital Twin-A Case on Formula 1 DSS

Andrew Greasley, Gajanan Panchal, Avinash Samvedi

Research output: Contribution to journal › Conference article › peer-review

Abstract

The implementation of a digital twin presents a challenging environment for simulation. One challenge is the need for fast execution speed to maintain synchronization with the real system. When providing predictive outcomes, the complementary use of simulation with machine learning and optimization software may be employed to achieve this aim. The article investigates the use of simulation, machine learning and optimization in terms of providing a digital twin capability. The article presents a case on Formula 1 or F1 competition, where a decision support system (DSS) framework is presented to explore a digital twin capability.

Original language	English
Number of pages	12
Journal	2022 Winter Simulation Conference (WSC)
DOIs	https://doi.org/10.1109/wsc57314.2022.10015299
Publication status	Published - 11 Dec 2022
Event	2022 Winter Simulation Conference - Online, Singapore Duration: 11 Dec 2022 → 14 Dec 2022 https://meetings.informs.org/wordpress/wsc2022/

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10.1109/wsc57314.2022.10015299

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abstract = "The implementation of a digital twin presents a challenging environment for simulation. One challenge is the need for fast execution speed to maintain synchronization with the real system. When providing predictive outcomes, the complementary use of simulation with machine learning and optimization software may be employed to achieve this aim. The article investigates the use of simulation, machine learning and optimization in terms of providing a digital twin capability. The article presents a case on Formula 1 or F1 competition, where a decision support system (DSS) framework is presented to explore a digital twin capability.",

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AB - The implementation of a digital twin presents a challenging environment for simulation. One challenge is the need for fast execution speed to maintain synchronization with the real system. When providing predictive outcomes, the complementary use of simulation with machine learning and optimization software may be employed to achieve this aim. The article investigates the use of simulation, machine learning and optimization in terms of providing a digital twin capability. The article presents a case on Formula 1 or F1 competition, where a decision support system (DSS) framework is presented to explore a digital twin capability.

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UR - https://meetings.informs.org/wordpress/wsc2022/

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The Use of Simulation with Machine Learning and Optimization for a Digital Twin-A Case on Formula 1 DSS

Abstract

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