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 naive operating strategies, and validates the economic viability of single and multi-mode CEA production of distinct crop portfolios. (C) 2021 Elsevier Ltd. All rights reserved.

Automated summary

The novel methodology proposed in this study offers a robust design and scheduling approach for controlled environment agricultural systems, addressing multi-period risks and uncertainties. It enhances the system's robustness to market uncertainty, improves long-term economic benefits, and validates the economic viability of producing various crop portfolios.