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Optimization in Science and Engineering

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Cover of 'Optimization in Science and Engineering'

Table of Contents

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    Book Overview
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    Chapter 1 Piecewise Linear Classifiers Based on Nonsmooth Optimization Approaches
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    Chapter 2 Variational Inequality Models Arising in the Study of Viscoelastic Materials
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    Chapter 3 Neighboring Local-Optimal Solutions and Its Applications
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    Chapter 4 General Traffic Equilibrium Problem with Uncertainty and Random Variational Inequalities
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    Chapter 5 Computational Complexities of Optimization Problems Related to Model-Based Clustering of Networks
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    Chapter 6 On Distributed-Lag Modeling Algorithms by r-Convexity and Piecewise Monotonicity
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    Chapter 7 Poincaré-Type Inequalities for Green’s Operator on Harmonic Forms
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    Chapter 8 The Robustness Concern in Preference Disaggregation Approaches for Decision Aiding: An Overview
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    Chapter 9 Separation of Finitely Many Convex Sets and Data Pre-classification
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    Chapter 10 The Shortest Superstring Problem
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    Chapter 11 Computational Comparison of Convex Underestimators for Use in a Branch-and-Bound Global Optimization Framework
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    Chapter 12 A Quasi Exact Solution Approach for Scheduling Enhanced Coal Bed Methane Production Through CO2 Injection
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    Chapter 13 A Stochastic Model of Oligopolistic Market Equilibrium Problems
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    Chapter 14 Computing Area-Tight Piecewise Linear Overestimators, Underestimators and Tubes for Univariate Functions
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    Chapter 15 Market Graph and Markowitz Model
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    Chapter 16 Nonconvex Generalized Benders Decomposition
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    Chapter 17 On Nonsmooth Multiobjective Optimality Conditions with Generalized Convexities
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    Chapter 18 A Game Theoretical Model for Experiment Design Optimization
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    Chapter 19 A Supply Chain Network Game Theoretic Framework for Time-Based Competition with Transportation Costs and Product Differentiation
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    Chapter 20 On the Discretization of Pseudomonotone Variational Inequalities with an Application to the Numerical Solution of the Nonmonotone Delamination Problem
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    Chapter 21 Designing Groundwater Supply Systems Using the Mesh Adaptive Basin Hopping Algorithm
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    Chapter 22 Regularity of a Kind of Marginal Functions in Hilbert Spaces
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    Chapter 23 On Solving Optimization Problems with Hidden Nonconvex Structures
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    Chapter 24 Variational Principles in Gauge Spaces
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    Chapter 25 Brain Network Characteristics in Status Epilepticus
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    Chapter 26 A Review on Consensus Clustering Methods
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    Chapter 27 Influence Diffusion in Social Networks
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    Chapter 28 A New Exact Penalty Function Approach to Semi-infinite Programming Problem
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    Chapter 29 On the Statistical Models-Based Multi-objective Optimization
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Title
Optimization in Science and Engineering
Published by
Springer, New York, NY, January 2014
DOI 10.1007/978-1-4939-0808-0
ISBNs
978-1-4939-0807-3, 978-1-4939-0808-0
Editors

Themistocles M. Rassias, Christodoulos A. Floudas, Sergiy Butenko

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 23%
Lecturer 2 6%
Student > Doctoral Student 2 6%
Student > Master 2 6%
Student > Bachelor 2 6%
Other 4 13%
Unknown 12 39%
Readers by discipline Count As %
Engineering 6 19%
Mathematics 4 13%
Computer Science 3 10%
Biochemistry, Genetics and Molecular Biology 1 3%
Chemical Engineering 1 3%
Other 3 10%
Unknown 13 42%