Электронная книга: Stanislaw H. Zak «An Introduction to Optimization»

An Introduction to Optimization

Praise for the Third Edition«. . . guides and leads the reader through the learning path . . . [e]xamples are stated very clearly and the results are presented with attention to detail.» —MAA Reviews Fully updated to reflect new developments in the field, the Fourth Edition of Introduction to Optimization fills the need for accessible treatment of optimization theory and methods with an emphasis on engineering design. Basic definitions and notations are provided in addition to the related fundamental background for linear algebra, geometry, and calculus. This new edition explores the essential topics of unconstrainedoptimization problems, linear programming problems, and nonlinear constrained optimization. The authors also present an optimization perspective on global search methods and include discussions on genetic algorithms, particle swarm optimization, and the simulated annealing algorithm. Featuring an elementary introduction to artificial neural networks, convex optimization, and multi-objective optimization, the Fourth Edition also offers: A new chapter on integer programming Expanded coverage of one-dimensional methods Updated and expanded sections on linear matrix inequalities Numerous new exercises at the end of each chapter MATLAB exercises and drill problems to reinforce the discussed theory and algorithms Numerous diagrams and figures that complement the written presentation of key concepts MATLAB M-files for implementation of the discussed theory and algorithms (available via the book's website) Introduction to Optimization, Fourth Edition is an ideal textbook for courses on optimization theory and methods. In addition, the book is a useful reference for professionals in mathematics, operations research, electrical engineering, economics, statistics, and business.

Издательство: "John Wiley&Sons Limited"

ISBN: 9781118523698

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  • optimization — /op teuh meuh zay sheuhn/ 1. the fact of optimizing; making the best of anything. 2. the condition of being optimized. 3. Math. a mathematical technique for finding a maximum or minimum value of a function of several variables subject to a set of …   Universalium

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  • Ordinal optimization — In mathematical optimization, ordinal optimization is the maximization of functions taking values in a partially ordered set ( poset ). Ordinal optimization has applications in the theory of queuing networks. Contents 1 Mathematical foundations 1 …   Wikipedia

  • Multi-objective optimization — (or multi objective programming),[1][2] also known as multi criteria or multi attribute optimization, is the process of simultaneously optimizing two or more conflicting objectives subject to certain constraints. Multiobjective optimization… …   Wikipedia

  • Extremal optimization — (EO) is an optimization heuristic inspired by the Bak Sneppen model of self organized criticality from the field of statistical physics. This heuristic was designed initially to address combinatorial optimization problems such as the travelling… …   Wikipedia

  • Mathematical optimization — For other uses, see Optimization (disambiguation). The maximum of a paraboloid (red dot) In mathematics, computational science, or management science, mathematical optimization (alternatively, optimization or mathematical programming) refers to… …   Wikipedia

  • Ant colony optimization algorithms — Ant behavior was the inspiration for the metaheuristic optimization technique. In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be… …   Wikipedia

  • Particle swarm optimization — (PSO) is a swarm intelligence based algorithm to find a solution to an optimization problem in a search space, or model and predict social behavior in the presence of objectives.OverviewParticle swarm optimization is a stochastic, population… …   Wikipedia

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