A Tabu Search Approach to Fuzzy Optimization of Camellia Oleifera Fertilization

Traditional optimization methods have been applied for years to high-yield fertilization models, which are usually well formulated by crisp coefficients and variables. Unfortunately, real-world crop growing environment and process are often not deterministic. In this paper we establish a fuzzy mathematical model between Camellia oleifera yield and fertilization application rates, in which variation coefficients of N, P, K are described with fuzzy numbers. In particular, we present a tabu search algorithm for finding a set of fertilization solutions in order to maximize Camellia oleifera yield based on fuzzy measures including expected value, optimistic value and pessimistic value. Our approach is more realistic and practical for real-world problems by taking vague and imprecise data into consideration, provides more comprehensive decision support by generating a set of high-quality alternatives, and can be applied to fertilizer decision for a variety of other crops.