scholarly journals Laying Hen Production Responses to Least Cost Rations Formulated with Stochastic Programming or Linear Programming with a Margin of Safety

1994 ◽  
Vol 73 (8) ◽  
pp. 1290-1295 ◽  
Author(s):  
T.L. CRAVENER ◽  
W.B. ROUSH ◽  
T.H. D’ALFONSO
Keyword(s):  
Linear Programming ◽  
Stochastic Programming ◽  
Laying Hen ◽  
Margin Of Safety

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.

scholarly journals A Risk-Aversion Approach for the Multiobjective Stochastic Programming Problem

Mathematics ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 2026
Author(s):  
Javier León ◽  
Justo Puerto ◽  
Begoña Vitoriano
Keyword(s):  
Linear Programming ◽  
Stochastic Programming ◽  
Value At Risk ◽  
Programming Model ◽  
Solution Concept ◽  
Linear Programming Model ◽  
Weighted Averaging ◽  
Conditional Value At Risk ◽  
Stochastic Knapsack ◽  
Ordered Weighted Averaging Operator

Multiobjective stochastic programming is a field that is well suited to tackling problems that arise in many fields: energy, financial, emergencies, among others; given that uncertainty and multiple objectives are usually present in such problems. A new concept of solution is proposed in this work, which is especially designed for risk-averse solutions. The proposed concept combines the notions of conditional value-at-risk and ordered weighted averaging operator to find solutions protected against risks due to uncertainty and under-achievement of criteria. A small example is presented in order to illustrate the concept in small discrete feasible spaces. A linear programming model is also introduced to obtain the solution in continuous spaces. Finally, computational experiments are performed by applying the obtained linear programming model to the multiobjective stochastic knapsack problem, gaining insight into the behaviour of the new solution concept.

Evaluation of Fuzzy Linear Programming Application in Energy Models

2013 ◽  
Vol 2 (1) ◽  
pp. 50-59 ◽  
Author(s):  
Mehdi Sadeghi ◽  
Hossein Mirshojaeian Hosseini
Keyword(s):  
Linear Programming ◽  
Stochastic Programming ◽  
Fuzzy Optimization ◽  
Energy Modeling ◽  
Fuzzy Linear Programming ◽  
Optimization Models ◽  
Energy Planning ◽  
Minimax Regret ◽  
Energy Models

Fuzzy Linear Programming (FLP) approach is an effective approach that has not been attended extensively by research and academic centers in energy planning field up to now. It seems that this inattention roots in some unknown and uninvestigated grounds about this approach that should be researched before any sectoral, regional, national or international applications. In this paper the authors tried to investigate different factors influence FLP modeling. Some factors challenge FLP application in energy modeling field. Other factors strengthen it as a serious competitor for other strategies under uncertainty like Stochastic Programming and Minimax Regret Strategy. Unfamiliarity of energy modelers and planners with this method, no favor of academic circles, confusion of modelers and planners stemmed from plurality of fuzzification and defuzzification methods and the lack of effective and comprehensive softwares for solving FLP problems are some of the obstacles against FLP application in energy planning field. In contrast, variant methods for different problems simplicity, flexibility, and possibility of FLP application in current supply energy models are strong points that propound FLP as an effective approach. Some remedies had been proposed to overcome these obstacles. Designing a software is a vital step. GAMS environment help us for this designation. Fuzzy GAMS is an idea to expand GAMS capabilities to fuzzy optimization models.

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