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Fast Solution of Discretized Optimization Problems

A collection of articles summarizing the state of knowledge in a large portion of modern homotopy th;...

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A Brief Introduction to Continuous Evolutionary Optimization

optimization problems. The hybridization of evolution strategies with local search allows fast optimization in solution spaces with many local optima;

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Optimization on Solution Sets of Common Fixed Point Problems

solution sets of common fixed point problems and convex feasibility problems. These optimization problems are investigated to determine good;

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Optimization on Solution Sets of Common Fixed Point Problems

solution sets of common fixed point problems and convex feasibility problems. These optimization problems are investigated to determine good;

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Pseudolinear Functions and Optimization

book describes the characterizations of solution sets of various optimization problems. It examines multiobjective pseudolinear, multiobjective;

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Pseudolinear Functions and Optimization

book describes the characterizations of solution sets of various optimization problems. It examines multiobjective pseudolinear, multiobjective;

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Parallel Random Search Algorithm

of the exact solution approaches is impossible due to large computational demands. Initially designed for unconstrained optimization, the variant;

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Optimization

Choose the Correct Solution Method for Your Optimization Problem Optimization: Algorithms and Applications presents a variety;

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Soft Computing Techniques for Engineering Optimization

. Features Explains the concept of optimization and relevance to soft computing techniques towards optimal solution;

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Soft Computing Techniques for Engineering Optimization

. Features Explains the concept of optimization and relevance to soft computing techniques towards optimal solution in engineering and;

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Optimization Modelling

approaches. The book demonstrates the use of optimization packages through the solution of various mathematical models and provides an interpretation;

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Scalable Algorithms for Contact Problems

This book presents a comprehensive and self-contained treatment of the authors' newly developed scalable algorithms for the solutions;

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Fast Sequential Monte Carlo Methods for Counting and Optimization

for estimation of rare-event probabilities, counting problems, and combinatorial optimization, Fast Sequential Monte Carlo Methods for;

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Advancing Parametric Optimization

uncertain data in an optimization problem is replaced with parameters, one obtains a multi-parametric optimization problem whose optimal solution;

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Optimization Techniques in Computer Vision

optimization gives the best solution based on numerical minimization of a single, scalar-valued objective function or cost function. Unconstrained;

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Optimization Methods in Finance

transaction costs and taxes. Chapters discussing the theory and efficient solution methods for the main classes of optimization problems alternate;

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Nonlinear Interval Optimization for Uncertain Problems

optimization models and solution algorithms. Lastly, it uses the proposed interval uncertain optimization models and methods to deal with practical;

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Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems

methodological and foundational issues from AI, OR, and algorithmics and present applications to the solution of combinatorial optimization problems;

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Stochastic Optimization Methods: Applications in Engineering and Operations Research

. In particular, it now shows how to apply stochastic optimization methods to the approximate solution of important concrete problems arising;

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Real-Time PDE-Constrained Optimization

difficulties. A particularly challenging class of PDE-constrained optimization problems is characterized by the need for real-time solution, i.e;

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Basic Control Volume Finite Element Methods For Fluids And Solids

solution so that it can be applied to both fluid flow and solid mechanics problems. To emphasize the essential ingredients, discussion focuses on;

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Applied Optimization MATLAB Programming

such as Multidisciplinary Optimization, Explicit Solution for Boundary Value Problems, and Particle Swarm Optimization.;

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The Linearization Method for Constrained Optimization

optimization specialists, from graduate student level on - a brief yet quite complete exposition of this most effective method of solution;

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Convexity And Optimization In Rn

algorithms for the solution of finite dimensional optimization problems. For readers who do not have the requisite background in real analysis, the;

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Nonlinear Analysis

Many of our daily-life problems can be written in the form of an optimization problem. Therefore, solution methods are needed to solve such;

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Foundations of Bilevel Programming

optimal solution for all parameter values, this problem is equivalent to a one-level optimization problem having an implicitly defined objective;

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Foundations of Bilevel Programming

optimal solution for all parameter values, this problem is equivalent to a one-level optimization problem having an implicitly defined objective;

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