| Description |
1 online resource (312 pages) : illustrations |
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text txt rdacontent |
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computer c rdamedia |
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online resource cr rdacarrier |
| Note |
Online resource, title from digital title page (viewed on October 8, 2020). |
| Contents |
Front Cover; Stochastic Global Optimization Methods and Applications to Chemical, Biochemical, Pharmaceutical and Environmental Processes; Stochastic Global Optimization Methods and Applications to Chemical, Biochemical, Pharmaceutical and Environmental Processe ... ; Copyright; Contents; About the authors; Preface; 1 -- Basic features and concepts of optimization; 1.1 Introduction; 1.2 Basic features; 1.2.1 Optimization and its benefits; 1.2.2 Scope for optimization; 1.2.3 Illustrative examples; 1.2.4 Essential requisites for optimization; 1.3 Basic concepts; 1.3.1 Functions in optimization |
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1.3.2 Interpretation of behavior of functions1.3.3 Maxima and minima of functions; 1.3.4 Region of search for constrained optimization; 1.4 Classification and general procedure; 1.4.1 Classification of optimization problems; 1.4.2 General procedure of solving optimization problems; 1.4.3 Bottlenecks in optimization; 1.5 Summary; References; 2 -- Classical analytical methods of optimization; 2.1 Introduction; 2.2 Statement of optimization problem; 2.3 Analytical methods for unconstrained single-variable functions; 2.3.1 Necessary and sufficient conditions |
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2.3.2 Sufficient conditions for convexity and concavity of a function2.4 Analytical methods for unconstrained multivariable functions; 2.4.1 Necessary and sufficient conditions; 2.4.2 Two-variable function; 2.4.3 Multivariable function; 2.5 Analytical methods for multivariable optimization problems with equality constraints; 2.5.1 Direct substitution; 2.5.2 Penalty function approach; 2.5.3 Method of Lagrange multipliers; 2.5.3.1 Necessary condition for a basic problem; 2.5.3.2 Necessary condition for a general problem; 2.5.3.3 Sufficient conditions for a general problem |
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2.6 Analytical methods for solving multivariable optimization problems with inequality constraints2.6.1 Kuhn-Tucker conditions for problems with inequality constraints; 2.6.2 Kuhn-Tucker conditions for problems with inequality and equality constraints; 2.7 Limitations of classical optimization methods; 2.8 Summary; References; 3 -- Numerical search methods for unconstrained optimization problems; 3.1 Introduction; 3.2 Classification of numerical search methods; 3.2.1 Direct search methods; 3.2.2 Gradient search methods; 3.3 One-dimensional gradient search methods; 3.3.1 Newton's method |
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3.3.2 Quasi-Newton method3.3.3 Secant method; 3.4 Polynomial approximation methods; 3.4.1 Quadratic interpolation method; 3.4.2 Cubic interpolation method; 3.5 Multivariable direct search methods; 3.5.1 Univariate search method; 3.5.2 Hooke-Jeeves pattern search method; 3.5.2.1 Exploratory move; 3.5.2.2 Pattern move; 3.5.3 Powell's conjugate direction method; 3.5.4 Nelder-Mead simplex method; 3.6 Multivariable gradient search methods; 3.6.1 Steepest descent method; 3.6.2 Multivariable Newton's method; 3.6.3 Conjugate gradient method; 3.7 Summary; References |
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4 -- Stochastic and evolutionary optimization algorithms |
| Bibliography |
Includes bibliographical references and index. |
| Subject |
Stochastic processes.
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Stochastic Processes |
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Processus stochastiques.
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Stochastic processes
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| Added Author |
Jujjavarapu, Satya Eswari.
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| Other Form: |
Print version: Venkateswarlu, Ch. Stochastic Global Optimization Methods and Applications to Chemical, Biochemical, Pharmaceutical and Environmental Processes. San Diego : Elsevier, ©2019 9780128173923 |
| ISBN |
9780128173930 |
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0128173939 |
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9780128173923 |
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0128173920 |
| Standard No. |
AU@ 000066283571 |
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