Budget allocation management model for seismic rehabilitation of infrastructure assets

• Main Author: Yadollahi, Mohammadreza
• Format: Thesis
• Language: English
• Published: 2013
• Subjects: TH Building construction
• Online Access: http://eprints.utm.my/id/eprint/37797/5/MohammadrezaYadollahiPFKA2013.pdf; http://eprints.utm.my/id/eprint/37797/

Economic efficiency is an important factor in seismic rehabilitation planning for infrastructure assets. An inventory of structures is screened to identify seismically susceptible parts and prioritize them in the order of need for rehabilitation purposes. In most cases, the financial resources for rehabilitation of infrastructure assets are limited. Therefore, there is a need to efficiently allocate such resources to various projects. The main goal of this research is to develop a budget allocation management model for rehabilitation of infrastructure projects, when there isn’t sufficient budget to allocate to all projects. Accordingly, a decision support system is developed and exercised in this research to optimize the budget for rehabilitation projects in three categories of road structures. To accomplish this, a computer-based Multiple Strategy Budget Allocation decision support System (MSBAS©) was developed to identify (including selection and prioritization) the best configuration (package) of seismic rehabilitation projects across existing structures. This system employs a multi-criteria assessment module that takes into account desirable criteria to estimate the financial needs for rehabilitation based on the existing budget constraints in a fiscal year. To select the optimal package of projects, a Genetic Algorithm (GA) optimization module is also developed. Multi-objective decision making is conducted under a specific decision strategy with solving a 0-1 Knapsack Problem. To demonstrate the applicability of the GA-based approach, a hypothetical decision making problem is presented. Using this system, managers can compare their decisions for different strategies and significantly improve management efficiency.