Last edited by Kajir
Monday, April 27, 2020 | History

7 edition of Global optimization found in the catalog.

Global optimization

deterministic approaches

by Reiner Horst

  • 1 Want to read
  • 8 Currently reading

Published by Springer in Berlin, New York .
Written in English

    Subjects:
  • Mathematical optimization,
  • Nonlinear programming

  • Edition Notes

    Includes bibliographical references (p. [681]-718) and index.

    StatementReiner Horst, Hoang Tuy.
    ContributionsHoang, Tuy, 1927-
    Classifications
    LC ClassificationsQA402.5 .H67 1996
    The Physical Object
    Paginationxviii, 727 p. :
    Number of Pages727
    ID Numbers
    Open LibraryOL981756M
    ISBN 103540610383, 3540560947
    LC Control Number96019368


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Global optimization by Reiner Horst Download PDF EPUB FB2

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The literature rarely discusses the tuning of. Springer is publishing the series “Optimization and Its Applications” aims to publish state-of-the-art expository works (monographs, contributed volumes, textbooks) that focus on algorithms for solving optimization problems and also study applications involving such problems.

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It focuses on Evolutionary Computation but also discusses other apporaches like Simulated Annealing and Extremal Optimization.5/5.

The Handbook of Global Optimization is the first comprehensive book to cover recent developments in global optimization.

Each contribution in the Handbook is essentially expository in nature, but scholarly in its treatment. The chapters cover optimality conditions, complexity results, concave minimization, DC programming, general quadratic.

Global optimization book   Deterministic global optimization. Dordrecht/Boston/London: Kluwer Academic Publishers. Search within book. Type for suggestions. Table of contents Previous. Page About this reference work. Introduction. Editors and affiliations. Bibliographic information.

Global Models. Global Optimization. Global Solution. Goal Constraints. Goal. Global optimization is the task of finding the absolutely best set of admissible conditions to achieve your objective, formulated in mathematical terms.

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Different ideas and methods proposed for global optimization are classified, described and discussed. The efficiency of algorithms is compared by using both artificial test problems and some practical problems. Global Optimization: Deterministic Approaches.

The main contents and character of the monograph did not change with respect to the first edition.2/5(1). Global optimization is a branch of applied mathematics and numerical analysis that attempts to find the global minima or maxima of a function or a set of functions on a given set.

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What is Global Optimization vs. Local Optimization. Global optimization refers to finding the optimal value of a given function among all possible solution whereas local optimization finds the optimal value within the neighboring set of candidate solution. Learn more in: From Optimization to Clustering: A Swarm Intelligence Approach.

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At other times, our perspective on a function might be more focused due to some restriction on its domain. Buy the Paperback Book Global Optimization in Engineering Design by Ignacio E. Grossmann atCanada's largest bookstore. Free shipping and pickup in store on eligible orders. Mathematical Programming has been of significant interest and relevance in engineering, an area that is very rich in challenging optimization problems.

Global optimization is a zone for the field of applied mathematics accompanied by analysis of data, it therefore deals with optimization (globally) of a function or remains dependent upon certain specific situations.

Distinctively, a group of bound and more common constraints along with the verdict variables are optimized and energy minimized taking into consideration the constraints. As our discussion of nonlinear programming unfolds, the reader is urged to reflect upon the linear- A general optimization problem is to select n decision variables x1,x2, Local vs.

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This is followed by a discussion of several illustrative examples which are based on real-world applications.

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Contents: 1. Fundamental Results --Convex Sets and Functions --General Properties of Optimization Problems --Convex Envelops --Kuhn-Tucker Conditions --Second Order Optimality Conditions --Duality in Nonlinear Programming --Complexity Issues.

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