Optimization under uncertainty in the era of big data and deep learning: When machine learning meets mathematical programming
C Ning, F You - Computers & Chemical Engineering, 2019 - Elsevier
This paper reviews recent advances in the field of optimization under uncertainty via a
modern data lens, highlights key research challenges and promise of data-driven …
modern data lens, highlights key research challenges and promise of data-driven …
Efficient methanol synthesis: Perspectives, technologies and optimization strategies
G Bozzano, F Manenti - Progress in Energy and Combustion Science, 2016 - Elsevier
In economy nowadays, methanol is already a key compound widely employed as building
block for producing intermediates or synthetic hydrocarbons, solvent, energy storage …
block for producing intermediates or synthetic hydrocarbons, solvent, energy storage …
[LIBRO][B] Nonlinear programming: concepts, algorithms, and applications to chemical processes
LT Biegler - 2010 - SIAM
Chemical engineering applications have been a source of challenging optimization
problems for over 50 years. For many chemical process systems, detailed steady state and …
problems for over 50 years. For many chemical process systems, detailed steady state and …
Quantum computing based hybrid solution strategies for large-scale discrete-continuous optimization problems
Quantum computing (QC) has gained popularity due to its unique capabilities that are quite
different from that of classical computers in terms of speed and methods of operations. This …
different from that of classical computers in terms of speed and methods of operations. This …
Forty years of heat integration: pinch analysis (PA) and mathematical programming (MP)
Highlights•Heat Integration (HI) has been an initial part of Process Integration (PI) for more
40 years now.•HI development has accelerated over the years.•The main two approaches …
40 years now.•HI development has accelerated over the years.•The main two approaches …
Global optimization advances in mixed-integer nonlinear programming, MINLP, and constrained derivative-free optimization, CDFO
This manuscript reviews recent advances in deterministic global optimization for Mixed-
Integer Nonlinear Programming (MINLP), as well as Constrained Derivative-Free …
Integer Nonlinear Programming (MINLP), as well as Constrained Derivative-Free …
Feedback control for optimal process operation
S Engell - Journal of process control, 2007 - Elsevier
In chemical process operation, the purpose of control is to achieve optimal process
operation despite the presence of significant uncertainty about the plant behavior and …
operation despite the presence of significant uncertainty about the plant behavior and …
A review of deterministic optimization methods in engineering and management
MH Lin, JF Tsai, CS Yu - Mathematical Problems in …, 2012 - Wiley Online Library
With the increasing reliance on modeling optimization problems in practical applications, a
number of theoretical and algorithmic contributions of optimization have been proposed. The …
number of theoretical and algorithmic contributions of optimization have been proposed. The …
Computationally efficient model predictive control algorithms
M Ławryńczuk - A Neural Network Approach, Studies in Systems …, 2014 - Springer
In the Proportional-Integral-Derivative (PID) controllers the control signal is a linear function
of: the current control error (the proportional part), the past errors (the integral part) and the …
of: the current control error (the proportional part), the past errors (the integral part) and the …
Polygeneration and efficient use of natural resources
The consumption of natural resources has been increasing continuously during recent
decades, due to the growing demand caused by both the economic and the demographic …
decades, due to the growing demand caused by both the economic and the demographic …