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An approach to interval programming problems with left-hand-side stochastic coefficients: An application to environmental decisions analysis

机译:具有左手侧随机系数的区间规划问题的一种方法:在环境决策分析中的应用

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An interval programming with stochastic coefficients (IPSC) model is developed for planning of regional air quality management. The IPSC model incorporates stochastic coefficients with multivariate normal distributions within an interval parameter linear programming (ILP) framework. In IPSC, system uncertainties expressed as stochastic coefficients and intervals are addressed. Since stochastic coefficients are the left-hand-side (LHS) parameters of the constraints in IPSC, a left-hand-side chance-constrained programming (LCCP) method is developed to solve the problem. The developed IPSC model is applied to a regional air quality management system. Uncertainties in both abatement efficiencies expressed as stochastic coefficients and environmental standards expressed as intervals are reflected. Interval solutions associated with different violation probability levels and/or different environmental standards have been obtained. Air quality managers can thus analyze the solutions with appropriate combinations of the uncertainties and gain insight into the tradeoffs between the abatement costs and the risks of violating different environmental standards.
机译:开发了具有随机系数的区间规划(IPSC)模型,用于规划区域空气质量管理。 IPSC模型在区间参数线性规划(ILP)框架内合并了具有多元正态分布的随机系数。在IPSC中,解决了以随机系数和间隔表示的系统不确定性。由于随机系数是IPSC中约束条件的左侧(LHS)参数,因此开发了左侧机会约束编程(LCCP)方法来解决该问题。已开发的IPSC模型被应用于区域空气质量管理系统。反映了以随机系数表示的减排效率和以区间表示的环境标准的不确定性。已获得与不同违规概率水平和/或不同环境标准相关的时间间隔解决方案。因此,空气质量管理人员可以将不确定性进行适当的组合来分析解决方案,并洞悉减排成本与违反不同环境标准的风险之间的权衡。

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