Optimal design of controlled environment agricultural systems under market uncertainty

We present a novel methodology for the simultaneous robust design and scheduling of controlled environment agricultural (CEA) systems under multi-period risk. This problem is formulated as a semi-infinite program with several semi-infinite constraints pertaining to mean-variance risk exposure with uncertain covariance over each period in the planning horizon. The general model enables robust optimization of CEA systems for cultivation of any crop portfolio under any number of cultivation modes, with a solution that represents an optimal design and operating schedule that is robust to worst-case uncertainty. Therefore, this methodology provides a conservative basis for engineering and investment decision-making and represents, to our knowledge, the first robust optimization approach to CEA systems. Our approach effectively increases the robustness of CEA systems to market uncertainty, improves the long-term economics of CEA systems over naïve operating strategies, and validates the economic viability of single and multi-mode CEA production of distinct crop portfolios.