SUSTAINABLE INFRASTRUCTURE MODELING AND POLICY ANALYSES: CONSTRUCTION, ENERGY AND TRANSPORTATION INDUSTRIES

Abstract

Sustainable infrastructure operation assumes consideration of interrelated elements and problems within interacting industries in which the decisions made for one industry may affect those in interrelated industries. Problems related to global climate change and resource scarcity are main concerns for a society trying to build a sustainable infrastructure. These problems are targeted from many perspectives, including government-enforced policies and regulations that call for energy efficiency and transportation efficiency to build a sustainable infrastructure. There is a growing interest among engineers in accounting for sustainability under the impact of climate change policies that limit the amount of pollutants being released from projects and facilities. While specific problems can be targeted by specialists in each industry or field, an optimal sustainable solution will be very difficult to find if considered separately. Despite that directions for improvement are defined, the methods and techniques for reaching these specified goals are not yet well developed. Decision-makers do not have the necessary models to evaluate the impact of proposed carbon policies supporting sustainable infrastructure development. Yet, it is important to analyze the problem in a systematic fashion to find cost-efficient, technically well-designed and constructed and sustainable solutions. In this dissertation, an interdisciplinary approach is used with the aim of analyzing programs geared at reducing emissions and costs, and determining optimal allocation of resources along with profit maximization by developing and employing optimization, regression and game-theoretic models for the construction, energy and transportation industries. These models can be used by national, state, local and private agencies for assessing carbon-mitigation policies and low-cost carbon policy developments. Concepts from integer programming, multi-objective decision-making, bi-level programming, simulation and regression are employed in the development of models to support informed decision-making and policy analyses in the construction, transportation and energy sectors. The models incorporate industry-specific details covering engineering, economic and environmental aspects of sustainable practices. The application of these models to real-world case studies provides insights that will allow defined specific goals to be achieved in a cost-efficient way. Results of case studies were optimal and most importantly not intuitive.