scholarly journals From graphical to model‐based distillation column design: A McCabe‐Thiele‐inspired mathematical programming approach

AIChE Journal ◽  
2019 ◽  
Vol 65 (11) ◽  
Author(s):  
Lingxun Kong ◽  
Christos T. Maravelias
Keyword(s):  
Mathematical Programming ◽  
Distillation Column ◽  
Programming Approach ◽  
Model Based ◽  
Distillation Column Design ◽  
Mathematical Programming Approach ◽  
Column Design

scholarly journals gBoost: a mathematical programming approach to graph classification and regression

2008 ◽  
Vol 75 (1) ◽  
pp. 69-89 ◽  
Author(s):  
Hiroto Saigo ◽  
Sebastian Nowozin ◽  
Tadashi Kadowaki ◽  
Taku Kudo ◽  
Koji Tsuda
Keyword(s):  
Mathematical Programming ◽  
Programming Approach ◽  
Graph Classification ◽  
Mathematical Programming Approach ◽  
Classification And Regression

A MATHEMATICAL PROGRAMMING APPROACH FOR GENERATING ALTERNATIVES IN DISCRETE STRUCTURAL OPTIMIZATION

1997 ◽  
Vol 28 (1-2) ◽  
pp. 1-31 ◽  
Author(s):  
JOHN W. BAUGH ◽  
SHANNON C. CALDWELL ◽  
E. DOWNEY BRILL
Keyword(s):  
Mathematical Programming ◽  
Structural Optimization ◽  
Programming Approach ◽  
Mathematical Programming Approach

Short-Cut Techniques for Distillation Column Design and Control. 2. Column Operability and Control

1979 ◽  
Vol 18 (2) ◽  
pp. 203-210 ◽  
Author(s):  
J. M. Douglas ◽  
A. Jafarey ◽  
R. Seemann
Keyword(s):  
Distillation Column ◽  
Distillation Column Design ◽  
Column Design ◽  
And Control

scholarly journals Formulating Intuitionistic Fuzzy Regression Models: A Mathematical Programming Approach

2021 ◽  
Author(s):  
Sheng-Hsing Nien ◽  
Liang-Hsuan Chen
Keyword(s):  
Mathematical Programming ◽  
Regression Models ◽  
Fuzzy Regression ◽  
Distance Measures ◽  
Programming Approach ◽  
Mathematical Programming Problem ◽  
Explanatory Variables ◽  
Intuitionistic Fuzzy ◽  
Mathematical Programming Approach ◽  
Ordinary Regression

Abstract This study develops a mathematical programming approach to establish intuitionistic fuzzy regression models (IFRMs) by considering the randomness and fuzziness of intuitionistic fuzzy observations. In contrast to existing approaches, the IFRMs are established in terms of five ordinary regression models representing the components of the estimated triangular intuitionistic fuzzy response variable. The optimal parameters of the five ordinary regression models are determined by solving the proposed mathematical programming problem, which is linearized to make the resolution process efficient. Based on the concepts of randomness and fuzziness in the formulation processes, the proposed approach can improve on existing approaches’ weaknesses with establishing IFRMs, such as the limitation of symmetrical triangular membership (or non-membership) functions, the determination of parameter signs in the model, and the wide spread of the estimated responses. In addition, some numerical explanatory variables included in the intuitionistic fuzzy observations are also allowed in the proposed approach, even though it was developed for intuitionistic fuzzy observations. In contrast to existing approaches, the proposed approach is general and flexible in applications. Comparisons show that the proposed approach outperforms existing approaches in terms of similarity and distance measures.

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