Prioritizing the Components of Vulnerability in a Genetic Algorithms Minimization of Flood Risk

TL;DR

This paper compares two schemes for prioritizing flood vulnerability components and uses a genetic algorithm to optimize flood-resistant city designs based on these priorities.

Contribution

It introduces a method to incorporate component prioritization into genetic algorithms for flood risk minimization.

Findings

Effective prioritization schemes identified

Optimized flood-resistant city designs generated

Weighted vulnerability functions improve risk assessment

Abstract

We compare two prioritization schemes for the components of flooding vulnerability: urbanized area ration, literacy rate, mortality rate, poverty, radio/tv penetration, non-structural measures and structural measure. We prioritize the components, giving each a weight. We then express the vulnerability function as a weighted sum of its components. This weighted sum serves as the fitness function in a genetic algorithm, which comes up with the optimal design for a flood-resistant city.