Optimal Crops Selection using Multiobjective Evolutionary Algorithms

96 AI MAGAZINE An adequate use of land resources is an essential guarantee of sustainable development, and many authors have suggested different approaches (Chi-Mei et al. 2002; Stewart, Janssen, and van Herwijnen 2004; Matthews et al. 2000; Tsuruta, Hoshi, and Sugai 2001; Bocco, Sayago, and Tartara 2002). The optimal use of soils is the basis of all forms of sustainable land use, that is, agricultural land use that remains productive in the long term. There are many benefits of an optimal use of soils, such as a decrease of rural poverty, watershed protection, increased biodiversity, more sustainable agricultural production, and increased food security (Schroth and Sinclair 2003). Therefore, optimal soil use planning is an important problem with social, economic, and ecological implications. Cultivation areas are usually divided in parcels, each one becoming a production unit. Every year farmers have to decide what to plant in each parcel. This requires the analysis of tradeoffs between investments that have to be made, expected profits, economical risks, and environmental effects of cultivation (Schroth and Sinclair 2003). Sustainable agricultural soil use requires making the land available for farming as productive as possible while considering the environmental impact of the cultivation process. Under natural conditions, soils present chemical restrictions for crop development. Chemical soil tests are used to provide information about acidity and nutrient levels of each land parcel. According to the requirements of crops to be cultivated, it is usual to modify soil chemical characteristics, changing the quantity of nutrients and acidity through fertilizing and liming, making productive agriculture possible but affecting the quality of soils, groundwater repositories, and the overall environment (Johnson, Adams, and Perry 1991). Furthermore, economic restrictions may constrain farmers to use small quantities of mineral fertilizers or sometimes none at all,