DECISION SUPPORT SYSTEM FOR HYDROPONIC FARMING

Abstract

The demand for food supply is rapidly increasing all over the world because of the expanding global population. To satisfy the increased demand, food growers face challenges, such as limited access to water resources and agricultural land shrinkage. Those challenges have limited food production and hence, new farming methods have been introduced. Hydroponic farming is one of the new farming methods used to produce more crop yield per square meter compared to conventional farming. The advantage of this new method is that farming can take place in abandoned warehouses, old buildings, or shipping containers, and it uses up to 90% less water. This research aims to provide an optimized design for hydroponic farming. A mixed-integer linear programming model (MILP) is proposed that considers the main design and costs of hydroponic farms. Therefore, the proposed model aims to find the optimal system output (i.e., hydroponic farming yield in kg) and profit together with optimal fixed and variable costs of the farm. The model was validated using data collected and estimated for the case study. The optimal system output was found to be 5,288 kg of vegetables, and the optimal solution (profit) equaled $3893.99 with fixed and variable costs of $3750 and $1,510.7, respectively. A sensitivity analysis was carried out to study system behavior. Furthermore, hydroponic farming was compared with conventional open- field farming and it was found that hydroponic farming can produce up to 7.5 times more yield per square meter than conventional farming.

Date of Award	2020
Original language	American English
Awarding Institution	HBKU College of Science and Engineering