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Robust optimization (RO), as a recent optimization scheme, has soon been adopted in many practical systems (e.g., power, logistics and healthcare systems) to support their design, operations, and reliabilities. Conventionally, RO captures the concerned randomness by a (static) uncertainty set, and derives a solution that should perform well in any scenario within that set. Nevertheless, it has been observed that the decision maker’s choice will significantly affect behavior of the underlying random factors, leading to the notion of decision-dependent uncertainty (DDU). For example, DDU occurs in the capacity expansion of charging facilities, where the installation of new charging facilities inspires and attracts more customers’ demand, i.e., the phenomenon of the ``induced demand.’’

In this talk, we first review existing computational methods for two-stage RO with static uncertainty. An extension to deal with left-hand-side uncertainty in Unit Commitment problem will be demonstrated. Then, a set of new results, including a new generation of column-and-constraint generation method, for two-stage RO with DDU will be presented. A demonstration on using DDU to capture the induced demand and then to develop an RO-based hydrogen-electrical system planning model is presented. Numerical results will be provided that highlights the impact of the induced demand in practical systems.

Dr. Zeng is an Associate Professor of Industrial Engineering in the Swanson School of Engineering at the University of Pittsburgh where he teaches and conducts research discrete and robust optimization, with applications in logistics, energy, and healthcare systems. Prior to that, he worked as an assistant professor of Industrial and Management Systems Engineering at the University of South Florida. Through his research, Dr. Zeng has developed several analytical operational models and algorithms (e.g., column-and-constraint generation method and its variants) that have been widely applied in energy and other critical infrastructure systems, to address real design and operational issues and to hedge against risks and to achieve better reliability and security. He is a professional member of IISE, INFORMS and IEEE.