Abstract Production planning under uncertainty is considered as one of the most important problems in plant-wide optimization. In this article, first, a stochastic programming model with uniform distribution assumption is developed for refinery production planning under demand uncertainty, and then a hybrid programming model incorporating the linear programming model with the stochastic programming one by a weight factor is proposed. Subsequently, piecewise linear approximation functions are derived and applied to solve the hybrid programming model-under uniform distribution assumption. Case studies show that the linear approximation algorithm is effective to solve.the hybrid programming model, along with an error≤0.5% when the deviatiorgmean≤20%. The simulation results indicate that the hybrid programming model with an appropriate weight factor （0.1-0.2） can effectively improve the optimal operational strategies under demand uncertainty, achieving higher profit than the linear programming model and the stochastic programming one with about 1.3% and 0.4% enhancement, respectavely.
为优化化工企业生产计划,本文建立了化工过程生产计划优化的混合整数非线性规划(mixed integer nonlinear program- ming)模型,并给出相应的迭代求解算法,实际应用表明该算法可以有效的求解模型。应用该MINLP模型和求解算法,在石化企业生产计划图形建模优化系统(graphic I/O petrochemical industry modeling system,GIOPIMS)已经成功开发和实施的基础上,针对化工企业的特点,重新开发出适合化工企业使用的生产计划图形建模优化系统(graphic I/O chemical industry modeling system,GIOCIMS)。GIOCIMS的实施表明,该系统在化工企业中间产品外购或自产,中间产品外销或深加工,工艺路线选择和装置负荷等优化方面发挥了重要作用,获得显著的经济效益?。
