Optimization techniques I : : Continuous optimization / / Max Cerf.

This book in two volumes provides an overview of continuous, discrete and functional optimization techniques. This first volume is devoted to continuous optimization, which deals with problems with real variables, without or with constraints. After a reminder of the optimality conditions and their g...

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Bibliographic Details
Superior document:Title is part of eBook package: De Gruyter DG Plus PP Package 2023 Part 2
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Place / Publishing House:Les Ulis : : EDP Sciences, , [2023]
©2023
Year of Publication:2023
Language:English
Series:Current Natural Sciences
Online Access:
Physical Description:1 online resource (482 p.)
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Other title:Frontmatter --
Preface --
Introduction --
Table of contents --
1. Continuous optimization --
1.1 Formulation --
1.2 Numerical derivatives --
1.3 Problem reduction --
1.4 Global optimum --
1.5 Local optimum --
1.6 Conclusion --
2. Gradient-free optimization --
2.1 Difficult optimization --
2.2 One-dimensional optimization --
2.3 DIRECT method --
2.4 Nelder-Mead method --
2.5 Affine shaker --
2.6 CMAES --
2.7 Simulated annealing --
2.8 Research with tabu --
2.9 Particle swarms --
2.10 Ant colonies --
2.11 Evolutionary algorithms --
2.12 Conclusion --
3. Unconstrained optimization --
3.1 Newton’s method --
3.2 Quasi-Newton methods --
3.3 Line search --
3.4 Trust region --
3.5 Proximal methods --
3.6 Convergence --
3.7 Conclusion --
4. Constrained optimization --
4.1 Classification of methods --
4.2 Penalization --
4.3 Reduced gradient --
4.4 Sequential quadratic programming --
4.5 Interior point --
4.6 Augmented Lagrangian --
4.7 Conclusion --
5. Linear programming --
5.1 Simplex --
5.2 Interior point --
5.3 Conclusion --
Index --
Bibliography
Summary:This book in two volumes provides an overview of continuous, discrete and functional optimization techniques. This first volume is devoted to continuous optimization, which deals with problems with real variables, without or with constraints. After a reminder of the optimality conditions and their geometrical interpretation, the topics covered are:-gradient-free algorithms that can be applied to any type of function;-unconstrained algorithms based on Newton-type descent methods;-algorithms with constraints: penalization, primal, dual and primal-dual methods;-linear programming with the simplex method and interior point methods. The emphasis is on understanding the principles rather than on mathematical rigor. Each concept or algorithm is accompanied by a detailed example to help you grasp the main ideas. This book is the result of 30 years of experience and is intended for students, researchers and engineers wishing to acquire a general knowledge in the field of optimization.This book is the English translation of «Techniques d'optimisation tomes 1 et 2» which was part of the final selection of «Prix Roberval 2023» in the «Higher Education» category.
Format:Mode of access: Internet via World Wide Web.
ISBN:9782759831647
9783111178042
9783111319292
9783111318912
9783111319209
9783111318608
DOI:10.1051/978-2-7598-3164-7
Access:restricted access
Hierarchical level:Monograph
Statement of Responsibility: Max Cerf.