| Record Type: |
Electronic resources
: Monograph/item
|
| Title/Author: |
Fundamentals of optimization techniques with algorithms/ Sukanta Nayak. |
| Author: |
Nayak, Sukanta. |
| Published: |
London, United Kingdom ;Academic Press is an imprint of Elsevier, : 2020., |
| Description: |
1 online resource (xv, 305 p.) :ill. |
| [NT 15003449]: |
Front Cover -- Fundamentals of Optimization Techniques With Algorithms -- Copyright Page -- Dedication -- Contents -- Preface -- Acknowledgments -- 1. Introduction to optimization -- 1.1 Optimal problem formulation -- 1.1.1 Design variables -- 1.1.2 Constraints -- 1.1.3 Objective function -- 1.1.4 Variable bounds -- 1.2 Engineering applications of optimization -- 1.3 Optimization techniques -- Further reading -- 2. Linear programming -- 2.1 Formulation of the problem -- Practice set 2.1 -- 2.2 Graphical method -- 2.2.1 Working procedure -- Practice set 2.2 -- 2.3 General LPP |
| [NT 15003449]: |
2.3.1 Canonical and standard forms of LPP -- Practice set 2.3 -- 2.4 Simplex method -- 2.4.1 Reduction of feasible solution to a basic feasible solution -- 2.4.2 Working procedure of the simplex method -- Practice set 2.4 -- 2.5 Artificial variable techniques -- 2.5.1 Big M method -- 2.5.2 Two-phase method -- Practice set 2.5 -- 2.6 Duality Principle -- 2.6.1 Formulation of a dual problem -- 2.6.1.1 Formulation of a dual problem when the primal has equality constraints -- 2.6.1.2 Duality principle -- Practice set 2.6 -- 2.7 Dual simplex method -- 2.7.1 Working procedure for a dual simplex method |
| [NT 15003449]: |
Practice set 2.7 -- Further reading -- 3. Single-variable nonlinear optimization -- 3.1 Classical method for single-variable optimization -- 3.2 Exhaustive search method -- 3.3 Bounding phase method -- 3.4 Interval halving method --3.5 Fibonacci search method -- 3.6 Golden section search method -- 3.7 Bisection method -- 3.8 Newton-Raphson method -- 3.9 Secant method -- 3.10 Successive quadratic point estimation method -- Further reading -- 4. Multivariable unconstrained nonlinear optimization -- 4.1 Classical method for multivariable optimization |
| [NT 15003449]: |
4.1.1 Definition: rth differential of a function f(X) -- 4.1.2 Necessary condition -- 4.1.3 Sufficient condition -- 4.2 Unidirectional search method -- 4.3 Evolutionary search method -- 4.3.1 Box's evolutionary optimization method -- 4.4 Simplex search method -- 4.5 Hooke-Jeeves pattern search method -- 4.5.1 Exploratory move -- 4.5.2 Pattern move -- 4.6 Conjugate direction method -- 4.6.1 Parallel subspace property -- 4.6.2 Extended parallel subspace property -- 4.7 Steepest descent method -- 4.7.1 Cauchy's (steepest descent) method -- 4.8 Newton's method -- 4.9 Marquardt's method |
| [NT 15003449]: |
Practice set -- Further reading -- 5. Multivariable constrained nonlinear optimization -- 5.1 Classical methods for equality constrained optimization -- 5.1.1 Solution by direct substitution -- 5.1.2 Solution by the method of constrained variation -- 5.1.3 Solution by the method of Lagrange multipliers -- 5.1.3.1 Necessary conditions -- 5.1.3.2 Sufficient condition -- 5.2 Classical methods for inequality constrained optimization -- 5.3 Random search method -- 5.4 Complex method -- 5.4.1 Iterative procedure -- 5.5 Sequential linear programming -- 5.6 Zoutendijk's method of feasible directions |
| Subject: |
Mathematical optimization. - |
| Online resource: |
https://www.sciencedirect.com/science/book/9780128211267 |
| ISBN: |
9780128224922 |