Global Optimization [electronic resource] : Scientific and Engineering Case Studies /
Pintér, János D.editor.
Optimization models based on a nonlinear systems description often possess multiple local optima. The objective of global optimization (GO) is to find the best possible solution of multiextremal problems. Global Optimization: Selected Case Studies illustrates the applicability of GO modeling techniques and solution strategies to real-world problems. The contributed chapters cover a broad range of applications from agroecosystem management, assembly line design, bioinformatics, biophysics, black box systems optimization, cellular mobile network design, chemical process optimization, chemical product design, composite structure design, computational modeling of atomic and molecular structures, controller design for induction motors, electrical engineering design, feeding strategies in animal husbandry, the inverse position problem in kinematics, laser design, learning in neural nets, mechanical engineering design, numerical solution of equations, radiotherapy planning, robot design, and satellite data analysis. The solution strategies discussed encompass a range of practically viable methods, including both theoretically rigorous and heuristic approaches. Audience This book is intended for researchers and practitioners in academia, research and consulting organizations, and industry.
Description based upon print version of record.
A Global Optimization Strategy and Its Use in Solvent Design -- Feeding Strategies for Maximising Gross Margin in Pig Production -- Optimized Design of Dynamic Networks with Heuristic Algorithms -- A New Smoothing-Based Global Optimization Algorithm for Protein Conformation Problems -- Physical Perspectives on the Global Optimization of Atomic Clusters -- Efficient Global Geometry Optimization of Atomic and Molecular Clusters -- Computational Analysis of Human DNA Sequences: An Application of Artificial Neural Networks -- Determination of a Laser Cavity Field Solution Using Global Optimization -- Computational Experience with the Molecular Distance Geometry Problem -- Non Linear Optimization Models in Water Resource Systems -- Solving the Phase Unwrapping Problem by a Parametrized Network Optimization Approach -- Evolutionary Algorithms for Global Optimization -- Determining 3-D Structure of Spherical Viruses by Global Optimization -- A Collaborative Solution Methodology for Inverse Position Problem -- Improved Learning of Neural Nets Through Global Search -- Evolutionary Approach to Design Assembly Lines -- Agroecosystem Management -- Finding the Minimal Root of an Equation -- Optimization of Radiation Therapy Dose Delivery with Multiple Static Collimation -- Parallel Triangulated Partitioning for Black Box Optimization -- A Case Study: Composite Structure Design Optimization -- Neural Network Enhanced Optimal Self-tuning Controller Design for Induction Motors.
Optimization models based on a nonlinear systems description often possess multiple local optima. The objective of global optimization (GO) is to find the best possible solution of multiextremal problems. Global Optimization: Selected Case Studies illustrates the applicability of GO modeling techniques and solution strategies to real-world problems. The contributed chapters cover a broad range of applications from agroecosystem management, assembly line design, bioinformatics, biophysics, black box systems optimization, cellular mobile network design, chemical process optimization, chemical product design, composite structure design, computational modeling of atomic and molecular structures, controller design for induction motors, electrical engineering design, feeding strategies in animal husbandry, the inverse position problem in kinematics, laser design, learning in neural nets, mechanical engineering design, numerical solution of equations, radiotherapy planning, robot design, and satellite data analysis. The solution strategies discussed encompass a range of practically viable methods, including both theoretically rigorous and heuristic approaches. Audience This book is intended for researchers and practitioners in academia, research and consulting organizations, and industry.
Mathematical models.
Engineering.
Mathematical optimization.
Computer mathematics.
Applied mathematics.
Engineering mathematics.
Mathematical Modeling and Industrial Mathematics.
Science, Humanities and Social Sciences, multidisciplinary.
Engineering, general.
Optimization.
Computational Mathematics and Numerical Analysis.
Mathematical and Computational Engineering.