1.

Record Nr.

UNISA990000707440203316

Autore

ARDEMANI, Edoardo

Titolo

L' economia delle imprese

Pubbl/distr/stampa

Milano : Giuffré, 1982

Descrizione fisica

XI, 500 p. ; 25 cm

Disciplina

658.1

Soggetti

Imprese - Saggi

Collocazione

658.1 ARD 3/1 (IEP VI 159/I)

658.1 ARD 3/1a (IEP VI 159/I BIS)

Lingua di pubblicazione

Italiano

Formato

Materiale a stampa

Livello bibliografico

Monografia

2.

Record Nr.

UNINA9910814521403321

Autore

Yang Xin-She

Titolo

Engineering optimization : an introduction with metaheuristic applications / / Xin-She Yang

Pubbl/distr/stampa

Hoboken, NJ, : Wiley, c2010

ISBN

9786612707773

9781282707771

1282707779

9780470640425

0470640421

9780470640418

0470640413

Edizione

[1st ed.]

Descrizione fisica

1 online resource (377 p.)

Disciplina

620.001/5196

Soggetti

Heuristic programming

Mathematical optimization

Engineering mathematics

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa



Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Engineering Optimization: An Introduction with Metaheuristic Applications; CONTENTS; List of Figures; Preface; Acknowledgments; Introduction; PART I FOUNDATIONS OF OPTIMIZATION AND ALGORITHMS; 1 A Brief History of Optimization; 1.1 Before 1900; 1.2 Twentieth Century; 1.3 Heuristics and Metaheuristics; Exercises; 2 Engineering Optimization; 2.1 Optimization; 2.2 Type of Optimization; 2.3 Optimization Algorithms; 2.4 Metaheuristics; 2.5 Order Notation; 2.6 Algorithm Complexity; 2.7 No Free Lunch Theorems; Exercises; 3 Mathematical Foundations; 3.1 Upper and Lower Bounds; 3.2 Basic Calculus

3.3 Optimality3.3.1 Continuity and Smoothness; 3.3.2 Stationary Points; 3.3.3 Optimality Criteria; 3.4 Vector and Matrix Norms; 3.5 Eigenvalues and Definiteness; 3.5.1 Eigenvalues; 3.5.2 Definiteness; 3.6 Linear and Affine Functions; 3.6.1 Linear Functions; 3.6.2 Affine Functions; 3.6.3 Quadratic Form; 3.7 Gradient and Hessian Matrices; 3.7.1 Gradient; 3.7.2 Hessian; 3.7.3 Function approximations; 3.7.4 Optimality of multivariate functions; 3.8 Convexity; 3.8.1 Convex Set; 3.8.2 Convex Functions; Exercises; 4 Classic Optimization Methods I; 4.1 Unconstrained Optimization

4.2 Gradient-Based  Methods4.2.1 Newton's Method; 4.2.2 Steepest Descent Method; 4.2.3 Line Search; 4.2.4 Conjugate Gradient Method; 4.3 Constrained Optimization; 4.4 Linear Programming; 4.5 Simplex Method; 4.5.1 Basic Procedure; 4.5.2 Augmented Form; 4.6 Nonlinear Optimization; 4.7 Penalty Method; 4.8 Lagrange Multipliers; 4.9 Karush-Kuhn-Tucker Conditions; Exercises; 5 Classic Optimization Methods II; 5.1 BFGS Method; 5.2 Nelder-Mead Method; 5.2.1 A Simplex; 5.2.2 Nelder-Mead Downhill Simplex; 5.3 Trust-Region Method; 5.4 Sequential Quadratic Programming; 5.4.1 Quadratic Programming

5.4.2 Sequential Quadratic ProgrammingExercises; 6 Convex Optimization; 6.1 KKT Conditions; 6.2 Convex Optimization Examples; 6.3 Equality Constrained Optimization; 6.4 Barrier Functions; 6.5 Interior-Point Methods; 6.6 Stochastic and Robust Optimization; Exercises; 7 Calculus of Variations; 7.1 Euler-Lagrange Equation; 7.1.1 Curvature; 7.1.2 Euler-Lagrange Equation; 7.2 Variations with Constraints; 7.3 Variations for Multiple Variables; 7.4 Optimal Control; 7.4.1 Control Problem; 7.4.2 Pontryagin's Principle; 7.4.3 Multiple Controls; 7.4.4 Stochastic Optimal Control; Exercises

8 Random Number Generators8.1 Linear Congruential Algorithms; 8.2 Uniform Distribution; 8.3 Other Distributions; 8.4 Metropolis Algorithms; Exercises; 9 Monte Carlo Methods; 9.1 Estimating π; 9.2 Monte Carlo Integration; 9.3 Importance of Sampling; Exercises; 10 Random Walk and Markov Chain; 10.1 Random Process; 10.2 Random Walk; 10.2.1 ID Random Walk; 10.2.2 Random Walk in Higher Dimensions; 10.3 Lévy Flights; 10.4 Markov Chain; 10.5 Markov Chain Monte Carlo; 10.5.1 Metropolis-Hastings Algorithms; 10.5.2 Random Walk; 10.6 Markov Chain and Optimisation; Exercises

PART II METAHEURISTIC ALGORITHMS

Sommario/riassunto

An accessible introduction to metaheuristics and optimization, featuring powerful and modern algorithms for application across engineering and the sciences  From engineering and computer science to economics and management science, optimization is a core component for problem solving. Highlighting the latest developments that have evolved in recent years, Engineering Optimization: An



Introduction with Metaheuristic Applications outlines popular metaheuristic algorithms and equips readers with the skills needed to apply these techniques to their own optimization problems. With insigh

3.

Record Nr.

UNINA9911051729603321

Autore

Baracca, Angelo

Titolo

Scienza e industria 1848-1915 : gli sviluppi scientifici connessi alla seconda rivoluzione industriale / Angelo Baracca, Stefano Ruffo, Arturo Russo

Pubbl/distr/stampa

Roma ; Bari, : Edizioni Laterza, 1979

Descrizione fisica

XII, 354 p. : ill. ; 18 cm

Collana

Universale Laterza ; 505

Altri autori (Persone)

Russo, Arturo

Ruffo, Stefano

Disciplina

509

Locazione

FI1

Collocazione

F.D.i.0973

Lingua di pubblicazione

Italiano

Formato

Materiale a stampa

Livello bibliografico

Monografia