Abstract
This study develops a management optimization model for tomato, strawberry, and paprika smart farms in Korea. The constructed optimization model contains a production quantity prediction model and a first-fruit harvest week prediction model. Those two prediction models incorporate the impacts of major environmental variables such as indoor temperature, solar radiation quantity, and irrigation amount. An additional econometric model that forecasts product prices responding to the changes in the product-related media data as well market prices is also estimated. Farm managers may run our dynamic optimization model to maximize their expected yearly profits incorporating price forecasts and environmental variables. Our simulation study shows that combining the price forecast model with the optimization model increases farm revenues substantially.
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