Agricultural production planning approach based on interval fuzzy credibility-constrained bi-level programming and Nerlove supply response theory

被引:31
作者
Zhang, Fan [1 ]
Engel, Bernard A. [2 ]
Zhang, Chenglong [1 ]
Guo, Shanshan [1 ]
Guo, Ping [1 ,3 ]
Wang, Sufen [1 ]
机构
[1] China Agr Univ, Ctr Agr Water Res China, Tsinghuadong St 17, Beijing 100083, Peoples R China
[2] Purdue Univ, Dept Agr & Biol Engn, W Lafayette, IN 47907 USA
[3] Minist Agr & Rural Affairs, Wuwei Expt Stn Efficient Water Use Agr, Wuwei 733000, Peoples R China
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
Bi-level programming; Fuzzy credibility-constraint programming; Nerlove response supply theory; Agricultural production planning; IRRIGATION WATER ALLOCATION; MODEL; MANAGEMENT; SYSTEMS;
D O I
10.1016/j.jclepro.2019.06.096
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
When planning agricultural production, planting area and water allocation are two major subjects faced by decision makers. In this study, a framework integrated Nerlove supply response model (Nerlove model) and interval fuzzy credibility-constraint bi-level programming (IFCBP) model is developed for planning the agricultural production in arid and semi-arid regions. Through Nerlove model, the planning process of crop planting area was described as an economic problem for forecasting farmers' behavior rather than an optimization problem for allocating farmland resources, and the relationship between crop planting area and market price can be obtained and further provide credible future crop planting area information. The IFCBP model can not only deal with uncertainties presented as interval and fuzzy numbers but also examine the credibility of the constraints and handle tradeoffs between two-level decision makers. To solve the IFCBP model, a solution method based on the interval interactive algorithm and credibility-cut method is proposed. Then, to verify the validity of the developed framework and solving method for agricultural production planning, they were applied to a real-case in the middle reaches of the Heihe River basin, northwest China. The forecasting results obtained from Nerlove model have better performance in predicting the future planting area of corn and vegetable than wheat, indicating that wheat plays a more vulnerable role in the decision-making process of planting area owing to its higher substitutability. The results show that the proposed framework can tackle two-level decision makers' concerns under uncertainties featured as inexact and fuzzy numbers, which can help regional managers plan future resources effectively. Furthermore, a comparison was made between IFCBP and two corresponding single-level models in this study. The comparison indicates that the developed model provides an effective tradeoff between two decision makers from different decision-making levels in IFCBP. The developed framework provides managers an effective way to plan agricultural production in arid and semi-arid regions, and the developed model and related thinking may help solve similar problems. (C) 2019 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1158 / 1169
页数:12
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