Saudi Cultural Missions Theses & Dissertations
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Item Restricted SERVICE NETWORK OPTIMIZATION TO GUIDE DECISIONS ON INFRASTRUCTURE INVESTMENT(George Mason University, 2023-12-13) Alyahya, Bedor; Brodsky, AlexanderInterrelated infrastructures, such as manufacturing, supply chain, renewable energy and smart grid, are critical for achieving long-term organizational and societal goals and enabling future growth. Deciding on infrastructure portfolio investment is a complex problem, given the uncertainty in future supply and demand, the rapid emergence of new technologies, and non-trivial operational interactions among the infrastructure components. Today, models and systems supporting stakeholders in infrastructure investment decisions either (1) express the investment model in high-level financial terms, which fails to accurately express the underlying operational system behavior over the investment time horizon, or (2) are hard- wired to a siloed domain-specific investment problem, which does not take into account interactions with interrelated infrastructures across the silos and inhibits the widespread adoption and re-usability of these models. Thus, both accurate and flexible investment decision models and systems are needed to recommend investment alternatives and guide stakeholders in making Pareto-optimal trade-o↵s between competing performance indicators such as total cost of ownership, carbon emissions and quality of service. This dissertation is driven by the need to overcome the aforementioned gap of investment decisions made in silos, as opposed to accounting for the synergistic value of strongly interdependent infrastructures. More specifically, the key contributions of this dissertation are as follows. First, designed and developed are formal predictive Analytic Models (AM) for both steady-state and tran- sient Service Networks. These models express metrics, capacity, and demand constraints over a specified time horizon as functions of fixed and controllable parameters, representing investment choices and precise operational settings throughout investment periods. Second, developed is a modular, extensible repository of investment component models, such as pumps, renewable energy sources, water and energy storage, Reverse Osmosis plants, transformers, energy contracts and electric and gas boilers, renewable energy certificates (RECs) and carbon o↵sets. Third, designed and developed are Decision Guidance Systems for both steady-state and transient models for investment in Service Networks. These systems optimize performance metrics and analyze Pareto-optimal trade-o↵s between di↵erent financial, environmental, and quality-of-service investment objectives leveraging a mixed-integer linear programming solver. As a specialization in the domain of Energy and Sustainability, developed is the Green Assessment and Decision Guidance Tool (GADGET.) Finally, a case study is conducted to provide recommendations to George Mason Uni- versity’s stakeholders on the most cost-e↵ective approach to achieve its carbon neutrality goals by 2040. GADGET provides recommendations for Pareto-optimal operational settings and investment choices related to the integration of renewable energy sources and related infrastructures with existing systems.4 0