ABSTRACT
This work presents an integrated system that can help engineers search for the optimal maintenance strategy for deteriorating RC buildings via multi-objective optimization. This system applies Particle Swarm Optimization (PSO) and the Pareto optimal solution to achieve the optimization of the multiple objectives of minimal LCCs (economy), minimal failure probability of the building (safety), minimal spalling probability of concrete cover (serviceability), maximum rationality, and minimal maintenance times. Additionally, to enhance computing efficiency in optimization, probabilistic effect assessment models for setting repair and retrofitting strategies are proposed. The proposed system has four main modules: (1) Deterioration analysis; (2) Seismic performance assessment; (3) Setting maintenance strategies; and (4) Multi-objective optimization. These four modules are integrated into the https://www.w3.org/1998/Math/MathML"> ⌜ https://s3-euw1-ap-pe-df-pch-content-public-p.s3.eu-west-1.amazonaws.com/9780429227196/8b5c0a5d-ddea-4c88-8eea-7152f7afb008/content/eq10864.tif" xmlns:xlink="https://www.w3.org/1999/xlink"/> Multi-objective Decision-making Support System for Maintenance Strategies for Deteriorating Reinforced Concrete Buildings https://www.w3.org/1998/Math/MathML"> ⌟ https://s3-euw1-ap-pe-df-pch-content-public-p.s3.eu-west-1.amazonaws.com/9780429227196/8b5c0a5d-ddea-4c88-8eea-7152f7afb008/content/eq10865.tif" xmlns:xlink="https://www.w3.org/1999/xlink"/> (MDMS-RCB). Finally, a case study is conducted to demonstrate application of the proposed system.
