A new class of agricultural production planning chance-constrained model with fuzzy parameters

This paper presents how credibility theory and chance-constrained optimization method can be efficiently applied for modelling and solving agricultural production planning problem in fuzzy systems. Since the proposed fuzzy agricultural production planning chance-constrained model includes fuzzy variable coefficients defined through possibility distributions with infinite supports, it is infinite-dimensional optimization problem that can rarely be solved directly via conventional optimization algorithms. The approximation of the fuzzy agricultural production planning problem is discussed in this paper, and we will design a heuristic algorithm, which combines approximation approach (AA), neural network (NN) and genetic algorithm (GA) to solve this agricultural production planning chance-constrained model with fuzzy parameters. Finally, one numerical example is given to show the feasibility and effectiveness of the proposed heuristic algorithm.