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Nonlinear Programming
A comprehensive treatment of nonlinear programming concepts and algorithms, especially as they apply to challenging applications in chemical process engineering.
Control and Optimization with Differential-Algebraic Constraints
A cutting-edge guide to modelling complex systems with differential-algebraic equations, suitable for applied mathematicians, engineers and computational scientists.
Large-Scale Optimization with Applications
With contributions by specialists in optimization and practitioners in the fields of aerospace engineering, chemical engineering, and fluid and solid mechanics, the major themes include an assessment of the state of the art in optimization algorithms as well as challenging applications in design and control, in the areas of process engineering and systems with partial differential equation models.
Large-Scale Optimization with Applications
With contributions by specialists in optimization and practitioners in the fields of aerospace engineering, chemical engineering, and fluid and solid mechanics, the major themes include an assessment of the state of the art in optimization algorithms as well as challenging applications in design and control, in the areas of process engineering and systems with partial differential equation models.
Systematic Methods of Chemical Process Design
Over the last 20 years, fundamental design concepts and advanced computer modeling have revolutionized process design for chemical engineering. Team work and creative problem solving are still the building blocks of successful design, but new design concepts and novel mathematical programming models based on computer-based tools have taken out much of the guess-work. This book presents the new revolutionary knowledge, taking a systematic approach to design at all levels.
23 European Symposium on Computer Aided Process Engineering
This study aims at improving the solution efficiency of Mixed Integer Nonlinear Programming (MINLP) through parallelism. Unlike most conventional parallel implementations of MINLP solvers, which utilize multi-threads to share the burden in the serial mode, the proposed method combines hybrid algorithms running on different threads. Two types of algorithms are designed in a parallel structure. One is the Quesada and Grossman's LP/NLP based branch and bound algorithm (QG); the other is Tabu Search (TS). The proposed method attempts to minimize the search space through continuous communication and exchange of intermediate results from each thread. Three kinds of information are exchanged betwee...
Real-Time PDE-Constrained Optimization
“…a timely contribution to a field of growing importance. This carefully edited book presents a rich collection of chapters ranging from mathematical methodology to emerging applications. I recommend it to students as a rigorous and comprehensive presentation of simulation-based optimization and to researchers as an overview of recent advances and challenges in the field.” — Jorge Nocedal, Professor, Northwestern University.Many engineering and scientific problems in design, control, and parameter estimation can be formulated as optimization problems that are governed by partial differential equations (PDEs). The complexities of the PDEs—and the requirement for rapid solution—pos...
Large-Scale Inverse Problems and Quantification of Uncertainty
This book focuses on computational methods for large-scale statistical inverse problems and provides an introduction to statistical Bayesian and frequentist methodologies. Recent research advances for approximation methods are discussed, along with Kalman filtering methods and optimization-based approaches to solving inverse problems. The aim is to cross-fertilize the perspectives of researchers in the areas of data assimilation, statistics, large-scale optimization, applied and computational mathematics, high performance computing, and cutting-edge applications. The solution to large-scale inverse problems critically depends on methods to reduce computational cost. Recent research approache...
