An uncertainty fractional joint probability chance constraint programming is developed to process land use structure optimization under uncertainty. The model integrate uncertainty programming into fractional programming, and the uncertainty programming include interval programming, fuzzy programming, stochastic programming and joint probability chance constraint programming. The results of the study are a series of land use policies in multiple scenarios with interval and deterministic numbers. The advantage of the model include it can (1) effectively integrate the two objectives of economic benefit maximization and pollution minimization by the fractional programming; (2) effectively process the uncertainty by the corresponding uncertainty programming; (3) reflect the impact of uncertainty on system benefit, pollutant discharge, and land use structure policy; and (4) develop a series of possible scenarios and corresponding feasible plans. The results of the study can help planners or decision makers develop flexible land use policy to address the multi-objective problems of maximum, minimum, and uncertainty. The proposed method is universal and can be extended to other cases.

开发了不确定度分数联合概率机会约束规划程序，以处理不确定条件下的土地利用结构优化。该模型将不确定性规划整合到分数规划中，不确定性规划包括区间规划，模糊规划，随机规划和联合概率机会约束规划。研究的结果是一系列具有间隔和确定性数字的多种情况下的土地使用政策。该模型的优点包括：（1）通过分数规划有效地整合了经济利益最大化和污染最小化两个目标；（2）通过相应的不确定度编程有效地处理不确定度；（3）反映不确定性对系统效益，污染物排放的影响；土地使用结构政策；（4）制定一系列可能的方案和相应的可行计划。研究结果可以帮助规划者或决策者制定灵活的土地使用政策，以解决最大，最小和不确定性的多目标问题。所提出的方法是通用的，并且可以扩展到其他情况。