Recent Progress in Two-stage Mixed-integer Stochastic Programming with Applications to Power Production Planning

2010 ◽  
pp. 177-208 ◽  
Author(s):  
Werner Römisch ◽  
Stefan Vigerske
Keyword(s):  
Stochastic Programming ◽  
Production Planning ◽  
Recent Progress ◽  
Power Production ◽  
Mixed Integer ◽  
Two Stage ◽  
Integer Stochastic Programming

Application of the Two-Stage Stochastic Programming for Optimizing Chemical Production Planning under Uncertainties

2009 ◽  
Vol 42 (6) ◽  
pp. 433-440 ◽  
Author(s):  
Chu-Fu Li ◽  
Lai-Xi Zou ◽  
Bing-Zhen Chen ◽  
Xiao-Rong He ◽  
Chun-Jian Dong ◽  
...  
Keyword(s):  
Stochastic Programming ◽  
Production Planning ◽  
Chemical Production ◽  
Two Stage

scholarly journals Scenario Based Two-Stage Stochastic Programming Approach for the Midterm Production Planning of Oil Refinery

MATEMATIKA ◽  
2018 ◽  
Vol 34 (3) ◽  
pp. 45-55 ◽  
Author(s):  
Norshela Mohd Noh ◽  
Arifah Bahar ◽  
Zaitul Marlizawati Zainuddin
Keyword(s):  
Linear Programming ◽  
Stochastic Programming ◽  
Production Planning ◽  
Oil Price ◽  
Profit Margin ◽  
Oil Refinery ◽  
Scenario Tree ◽  
Programming Approach ◽  
Two Stage ◽  
The Past

Recently, oil refining industry is facing with lower profit margin due to uncertainty. This causes oil refinery to include stochastic optimization in making a decision to maximize the profit. In the past, deterministic linear programming approach is widely used in oil refinery optimization problems. However, due to volatility and unpredictability of oil prices in the past ten years, deterministic model might not be able to predict the reality of the situation as it does not take into account the uncertainties thus, leads to non-optimal solution. Therefore, this study will develop two-stage stochastic linear programming for the midterm production planning of oil refinery to handle oil price volatility. Geometric Brownian motion (GBM) is used to describe uncertainties in crude oil price, petroleum product prices, and demand for petroleum products. This model generates the future realization of the price and demands with scenario tree based on the statistical specification of GBM using method of moment as input to the stochastic programming. The model developed in this paper was tested for Malaysia oil refinery data. The result of stochastic approach indicates that the model gives better prediction of profit margin.

Monotonic bounds in multistage mixed-integer stochastic programming

2016 ◽  
Vol 13 (3) ◽  
pp. 423-457 ◽  
Author(s):  
Francesca Maggioni ◽  
Elisabetta Allevi ◽  
Marida Bertocchi
Keyword(s):  
Stochastic Programming ◽  
Mixed Integer ◽  
Integer Stochastic Programming
Sign in / Sign up

Export Citation Format

Share Document