Surrogate-based decision-making of community building portfolios under uncertain consequences and risk attitudes

Abstract

The performance of community building portfolios under extreme events is increasingly been assessed in terms of socioeconomic and environmental consequences. These multiple consequences are expensive to be evaluated, uncertain in nature, and it requires an efficient optimization and decision-making tool for performance enhancements on a community level. In this paper, an efficient multi-objective performance-based optimization and decision-making framework is proposed to assess and enhance the performance of community building portfolios under uncertain consequences. The proposed approach includes (1) performance-based black-box to evaluate the socioeconomic and environmental consequences given community building portfolios by considering all the possible hazard scenarios, (2) surrogate-based multi-objective optimization to efficiently approximate the Pareto-optimal solutions by exploiting Gaussian process models, spectral sampling, non-dominated crowding and sorting, and hyper improvements, among others, and (3) utility theory-based decision-making of a community building portfolios considering multiple performance-objectives over an entire hazard curve and under different risk attitudes. The proposed methodology is illustrated on community building portfolio under seismic hazards of varying intensities and occurrence probabilities. A performance-based black box is utilized along with a proposed optimization technique to assess community-level consequences. Finally, the utility for Pareto-optimal solutions is assessed and discussed for possible performance enhancements and decision-making.