## Optimization Techniques and Applications with Examples
Designed as a practical resource, all topics are explained in detail with step-by-step examples to show how each method works. The book’s exercises test the acquired knowledge that can be potentially applied to real problem solving. By taking an informal approach to the subject, the author helps readers to rapidly acquire the basic knowledge in optimization, operational research, and applied data mining. This important resource: - Offers an accessible and state-of-the-art introduction to the main optimization techniques
- Contains both traditional optimization techniques and the most current algorithms and swarm intelligence-based techniques
- Presents a balance of theory, algorithms, and implementation
- Includes more than 100 worked examples with step-by-step explanations
Written for upper undergraduates and graduates in a standard course on optimization, operations research and data mining, |

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### Contents

Mathematical Foundations | 3 |

5 | 32 |

Algorithms Complexity and Convexity | 37 |

Optimization Techniques and Algorithms | 63 |

Constrained Optimization | 87 |

Approximation Methods | 103 |

Applied Optimization | 125 |

7 | 129 |

Regularization and Lasso Method | 186 |

Exercises | 195 |

Queueing Theory and Simulation | 227 |

Advanced Topics | 249 |

k Exercises | 266 |

Evolutionary Computation and NatureInspired | 279 |

NatureInspired Algorithms | 297 |

Appendix A Notes on Software Packages | 323 |