## An Introduction to OptimizationPraise from the Second Edition"...an excellent introduction to optimization theory..." ( "A textbook for a one-semester course on optimization theory and methods at the senior undergraduate or beginning graduate level." (
Optimization is central to any problem involving decision making in many disciplines, such as engineering, mathematics, statistics, economics, and computer science. Now, more than ever, it is increasingly vital to have a firm grasp of the topic due to the rapid progress in computer technology, including the development and availability of user-friendly software, high-speed and parallel processors, and networks. Fully updated to reflect modern developments in the field, The book begins with a review of basic definitions and notations and also provides the related fundamental background of linear algebra, geometry, and calculus. With this foundation, the authors explore the essential topics of unconstrained optimization problems, linear programming problems, and nonlinear constrained optimization. An optimization perspective on global search methods is featured and includes discussions on genetic algorithms, particle swarm optimization, and the simulated annealing algorithm. In addition, the book includes an elementary introduction to artificial neural networks, convex optimization, and multi-objective optimization, all of which are of tremendous interest to students, researchers, and practitioners. Additional features of the -
New discussions of semidefinite programming and Lagrangian algorithms -
A new chapter on global search methods -
A new chapter on multipleobjective optimization -
New and modified examples and exercises in each chapter as well as an updated bibliography containing new references -
An updated Instructor's Manual with fully worked-out solutions to the exercises
Numerous diagrams and figures found throughout the text complement the written presentation of key concepts, and each chapter is followed by MATLAB exercises and drill problems that reinforce the discussed theory and algorithms. With innovative coverage and a straightforward approach, |

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### Contents

CHAPTER 4CONCEPTS FROM GEOMETRY | |

CHAPTER 5ELEMENTS OF CALCULUS | |

EXERCISES | |

CHAPTER 7ONEDIMENSIONAL SEARCH METHODS | |

CHAPTER 8GRADIENT METHODS | |

CHAPTER 13UNCONSTRAINED OPTIMIZATION | |

EXERCISES | |

EXERCISES | |

PROGRAMMING | |

EXERCISES | |

CHAPTER 17DUALITY | |

CHAPTER 18NONSIMPLEX METHODS | |

CHAPTER 19PROBLEMS WITH EQUALITY CONSTRAINTS | |

CHAPTER 9NEWTONS METHOD | |

EXERCISES | |

CHAPTER 10CONJUGATE DIRECTIONMETHODS | |

CHAPTER 11QUASINEWTON METHODS | |

EXERCISES | |

CHAPTER 12SOLVING LINEAR EQUATIONS | |

CHAPTER 21CONVEX OPTIMIZATION PROBLEMS | |

CHAPTER 22ALGORITHMS FOR CONSTRAINED | |

CHAPTER 23MULTIOBJECTIVE OPTIMIZATION | |