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In the proposed fuzzy crop production planning VaR model, the profit coefficients are imprecise uncertain and assumed to be fuzzy variables with known possibility distributions. Due to the fuzzy variable parameters with infinite supports, the VaR model is inherently an infinite-dimensional optimization problem that can rarely be solved directly via conventional mathematical programming methods. Therefore, algorithm procedures for solving this optimization problem must rely on approximation schemes and heuristic computing. The paper presents a heuristic algorithm, which integrates approximation approach (AA), neural network (NN) and genetic algorithm (GA), to solve the fuzzy crop production planning VaR model. 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