A Hybrid Programming Model for Optimal Production Planning under Demand Uncertainty in Refinery

李初福; 何小荣; 陈丙珍; 徐强; 刘朝玮

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A Hybrid Programming Model for Optimal Production Planning under Demand Uncertainty in Refinery

Updated：2026-01-06

- A Hybrid Programming Model for Optimal Production Planning under Demand Uncertainty in Refinery
- A Hybrid Programming Model for Optimal Production Planning under Demand Uncertainty in Refinery
- 中国化学工程学报（英文版） 2008年16卷第2期页码：241-246
- Affiliations：
  
  1. Department of Chemical Engineering, Tsinghua University,Beijing,China,100084
  2. Department of Chemical Engineering, Lamar University, Beaumont,USA,77710
- Author bio：
- Funds：
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  中图分类号：
- 纸质出版：2008
- Accepted：
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李初福, 何小荣, 陈丙珍, 等. A Hybrid Programming Model for Optimal Production Planning under Demand Uncertainty in Refinery[J]. 中国化学工程学报（英文版）, 2008,16(2):241-246.

LI Chufu, HE Xiaorong, CHEN Bingzhen, XU Qiang, LIU Chaowei. A Hybrid Programming Model for Optimal Production Planning under Demand Uncertainty in Refinery[J]. , 2008, 16(2): 241-246.
李初福, 何小荣, 陈丙珍, 等. A Hybrid Programming Model for Optimal Production Planning under Demand Uncertainty in Refinery[J]. 中国化学工程学报（英文版）, 2008,16(2):241-246. DOI：

LI Chufu, HE Xiaorong, CHEN Bingzhen, XU Qiang, LIU Chaowei. A Hybrid Programming Model for Optimal Production Planning under Demand Uncertainty in Refinery[J]. , 2008, 16(2): 241-246. DOI：

摘要

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 deviation/mean≤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 lin-ear programming model and the stochastic programming one with about 1.5% and 0.4% enhancement

respectively.

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