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 |
|---|---|
| Title of host publication | 2022 Winter Simulation Conference (WSC) |
| Publisher | IEEE |
| Number of pages | 12 |
| ISBN (Electronic) | 978-1-6654-7661-4 |
| ISBN (Print) | 978-1-6654-7662-1 |
| DOIs | |
| 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/ |
Publication series
| Name | 2022 Winter Simulation Conference (WSC) |
|---|---|
| Publisher | IEEE |
| ISSN (Print) | 0891-7736 |
| ISSN (Electronic) | 1558-4305 |
Conference
| Conference | 2022 Winter Simulation Conference |
|---|---|
| Abbreviated title | WSC |
| Country/Territory | Singapore |
| Period | 11/12/22 → 14/12/22 |
| Internet address |