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OPTIMIZATION CONCEPTS AND APPLICATIONS IN ENGINEERING 3E
Título:
OPTIMIZATION CONCEPTS AND APPLICATIONS IN ENGINEERING 3E
Subtítulo:
Autor:
BELEGUNDU, A
Editorial:
CAMBRIDGE UNIVERSITY PRESS
Año de edición:
2019
Materia
INGENIERIA DE CONTROL - GENERAL
ISBN:
978-1-108-42488-2
Páginas:
464
136,94 €

 

Sinopsis

Organizations and businesses strive toward excellence, and solutions to problems are based mostly on judgment and experience. However, increased competition and consumer demands require that the solutions be optimum and not just feasible. Theory leads to algorithms. Algorithms need to be translated into computer codes. Engineering problems need to be modeled. Optimum solutions are obtained using theory and computers, and then interpreted. Revised and expanded in its third edition, this textbook integrates theory, modeling, development of numerical methods, and problem solving, thus preparing students to apply optimization to real-world problems. This text covers a broad variety of optimization problems using: unconstrained, constrained, gradient, and non-gradient techniques; duality concepts; multi-objective optimization; linear, integer, geometric, and dynamic programming with applications; and finite element-based optimization. It is ideal for advanced undergraduate or graduate courses in optimization design and for practicing engineers.

Teaches a variety of optimization topics in a manner that integrates theory, algorithms, modeling, and computer implementation
Gives students hands-on experience by providing in-house source codes in MATLAB®, JavaScript, Excel VBA, and Fortran, and also shows how readily available commercial software (Excel SOLVER and MATLAB® routines) can be used
Useful for students in academia as well as for practicing engineers, as solved examples teach how to tackle realistic engineering optimization problems
Provides detailed explanations of all concepts and solution algorithms



Table of Contents

Preface
1. Preliminary concepts
2. One-dimensional unconstrained minimization
3. Unconstrained optimization
4. Linear programming
5. Constrained minimization
6. Penalty functions, duality, and geometric programming
7. Direct search methods for nonlinear optimization
8. Multi-objective optimization
9. Integer and discrete programming
10. Dynamic programming
11. Optimization applications for transportation, assignment, and network problems
12. Finite element and simulation-based optimization
Index.