Metamodel-based metaheuristics in optimal responsive adaptation and recovery of traffic networks

Metamodel-based metaheuristics in optimal responsive adaptation and recovery of traffic networks

Teixeira, Rui (University College Dublin)
Martinez-Pastor, Beatriz (University College Dublin)
Nogal Macho, M. (TU Delft Integral Design & Management)
O’Connor, Alan (Trinity College Dublin)

2022

Different emerging threats highlighted the relevance of recovery and adaptation modelling in the functioning of societal systems. However, as modelling of systems becomes more complex, its effort increases challenging the practicality of the engineering analyses required for efficient recovery and adaptation. In the present work, metamodels are researched as a tool to enable these analyses in traffic networks. One of the main advantages of metamodeling is their synergy with the short decision times required in recovery and adaptation. A sequential global metamodeling technique is proposed and applied to three macroscopic day-to-day user-equilibrium models. Two reference contexts of application are researched: optimal recovery to a perturbation (with response times reduced by 98% with loss of accuracy lower than 1%) and adaptation under uncertainty with perturbation-dependent optimality. Results show that metamodeling-based metaheuristics enable fast resource-intensive engineering analyses of traffic recovery and adaptation, which may change the paradigm of decision-making in this field.

Decision-making
Metamodeling
Resilience
System adaptation
System analysis
System recovery

http://resolver.tudelft.nl/uuid:6c91856b-7b44-4f82-a790-fdebb87d94ac

https://doi.org/10.1080/23789689.2022.2029325

2378-9689

Sustainable and Resilient Infrastructure, 7 (6), 756-774

Institutional Repository

journal article

© 2022 Rui Teixeira, Beatriz Martinez-Pastor, M. Nogal Macho, Alan O’Connor