Agricultural land allocation problem under dynamic environments in selling prices and planting costs is complicated. Preliminary study found that most farmers decide on what to plant based on either current selling prices or traditional crops planted in the past. Main objective of this study is to determine the optimal agricultural land allocation. Firstly, product prices during different time periods are forecasted. Linear programming is formulated to represent the problem. Dynamic programming is then applied to solve for the optimal plan. Case study is the agricultural land allocation in Phutthamonthon district, Nakornpathom province, Thailand with the wish to improve famer's standard of living. The analytical results found that the benefit from agricultural planning using dynamic programming is superior to the traditional ways.
