Over the past twenty years, food security and public health have become central to the overarching policies of governments worldwide. Within this framework, poverty reduction and food security are goals of sustainable development. In this regard, improving the income of the studied community is essential to improve various poverty indicators. In agriculture, this improvement can be achieved through effective resource management and selection of appropriate cropping patterns. This chapter begins by examining studies on food insecurity, followed by an overview of the indicators used to measure it and the introduction of the Foster-Greer-Thorbecke (FGT) poverty index. A mathematical programming model is then presented, aiming to optimize the FGT index by increasing income through the implementation of an optimal cropping pattern. An empirical study is conducted to evaluate food insecurity in Iranian provinces, showcasing the application of the index. Additionally, a case study was selected in several rural areas of Khuzestan province in Iran to test the capability of the proposed mathematical programming model. The findings indicate that food insecurity is more prevalent in urban areas compared to rural areas in Iran. Also, the proposed mathematical programming model can significantly help to reduce the poverty index by determining a new optimal cropping pattern.