Multi-objective optimisation of bridge retrofit and post-event repair selection to enhance sustainability

Abstract

The decaying state of our infrastructure paired with rising emphasis on sustainable engineering suggests the need for upgrades which are selected based on their ability to provide adequate performance under natural hazards and minimise negative impacts on the three pillars of sustainability: society, environment and economy. This paper poses a framework based on a multi-objective genetic algorithm to help identify optimal retrofit and repair combinations which ensure public safety while minimising lifetime environmental, economic and social performance measures of sustainability for infrastructure exposed to natural hazards. Assessment of the case-study application results reveals the relationship between life-cycle environmental, economic and social indicators of sustainability for a bridge subject to earthquakes. The framework is anticipated to help guide the selection of retrofit and repair combinations by providing a set of ‘near-optimal’ non-dominated solutions, which enhance sustainability while ensuring public safety and mitigating or repairing damage from natural disasters.

Keywords::

• sustainability
• multi-objective optimisation
• genetic algorithm
• risk assessment
• life-cycle analysis
• natural hazard mitigation
• triple bottom line

Acknowledgements

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Notes

^1. Email: [email protected]

Additional information

Funding

Disclosure statementNo potential conflict of interest was reported by the authors.The authors gratefully acknowledge the support of this research by the National Science Foundation (NSF) [grant number CMMI-1055301]. The first author acknowledges the support of NSF through the Graduate Research Fellowship Program [grant number 0940902].