ABSTRACT

In large-scale agriculture, insufficient irrigation water may lead to over-pumping of groundwater, increasing the risk of land subsidence. Growing dry land crops can effectively decrease the demand for irrigation water. However, the previous works on annual crop planting (ACP) focused on maximizing the profit through growing wetland crops, consuming much water. For sustainability, this project proposes a mathematical programming model for an ACP that allocates a land area for growing dry land and wetland crops to maximize the total profit and minimize the total irrigation water used for multiple cropping, under practical constraints. Simplified swarm optimization (SSO) improves the PSO with four probabilities to determine the operations of updating solutions. We further propose dynamic SSO to solve the concerned ACP, in which the four probabilities are adjusted dynamically according to performance of the operations executed. Through simulation on a case study, the proposed DSSO demonstrates high performance over some classical approaches.