Affiliations: [a] School of Management, Hebei University, Baoding, Hebei, China
| [b] Department of Fundamental Sciences, Hebei Finance University, Baoding, Hebei, China
| [c] School of Economics and Management, University of Chinese Academy of Sciences, Beijing, China
Correspondence:
[*]
Corresponding author. G. Yuan, Hebei Finance University, No. 3188, Hengxiang North Street, Baoding City, Hebei Province, 071051, China. Tel./Fax: +86 0312 3338261; E-mail: yggqq@126.com.
Abstract: This paper introduces the fuzzy Value-at-Risk (VaR) into crop production planning and proposes a risk-based decision-making approach to the problem in imprecise or fuzzy parameters environments. 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. Finally, a practical example is given to show the feasibility and effectiveness of the proposed model and heuristic algorithm.
