Sensitivity-based adaptive procedure (SAP) for optimal rehabilitation of sewer systems

ABSTRACT

Urban flood resilience requires high-performance sewer systems, and multi-objective optimization methods are widely used to improve sewer system efficiency. A non-polynomial complete (NP complete) optimization problem may exist in urban sewer rehabilitation, which may cause low efficiency in optimizing large network systems. In this research, a sensitivity-based adaptive procedure (SAP) is proposed, which can be integrated with optimization algorithms. SAP was integrated with Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Multiple Objective Particle Swarm Optimization (MOPSO) methods. We further used the Hydraulics and Risk Combined Model (HRCM), which is a risk-informed multi-objective optimization model designed for drainage system rehabilitation to validate the performance of SAP procedure. Results showed that SAP can improve the optimizing performance, and SAP-NSGA-II exhibited superior performance in solving the combined problems of pipe breakage and overflooding.

KEYWORDS:

• Adaptive optimization
• stormwater system
• rehabilitation
• urban flooding
• risk assessment

Acknowledgements

Authors would like to extend their appreciation to the editors and the reviewers who provided valuable feedback to this paper. We would also like to thank Zirou Qiu at the University of Virginia for his help with the combinatorial optimization.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability of statement

Some or all data, models, or code generated or used during the study are available from the corresponding author by request.

Supplementary material

Supplemental data for this article can be accessed https://doi.org/10.1080/1573062X.2022.2102509