Work

CRN_MultiHazard_MOEGO: A Kriging-Based Multi-Objective Efficient Global Optimization Framework for Proactive Rehabilitation Planning of Concrete Road Networks Under Multiple Hazards

Year: 2026

Type: software

Abstract: A reduced, reproducible case study accompanying the manuscript "Proactive Rehabilitation Planning for Concrete Road Networks Considering Multiple Hazards and Multiple Assets: A Kriging-based Multi-Objective Efficient Global Optimization Approach." Includes the Kriging-based Multi-Objective Efficient Global Optimization (MO-EGO) framework (surrogate model, optimizer, cost-based rehabilitation budget, network-processing routines) and the underlying high-fidelity earthquake/flood damage modeling and SUMO traffic-simulation engine (hazard-model settings, fragility parameters), for a concrete road network case study in Arden-Arcade, Sacramento, California.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.22834094

Authors: Adhikari, Sandesh, Roy, Abhijit, Sharveen, Sumaya, Bhatta, Sushil, Shahandashti, Mohsen

Institution: The University of Texas at Arlington

Language: English

Topic: Infrastructure Resilience and Vulnerability Analysis

Subfield: Civil and Structural Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities

Open Access status: green

OpenAlex ID: W7213601436

Cites:

Cited by:

Related to: 10