Introduction to Applied Optimization - Urmila Diwekar

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Résumé :
Provides well-written self-contained chapters, including problem sets and exercises, making it ideal for the classroom setting;



Introduces applied optimization to the hazardous waste blending problem;





Explores linear programming, nonlinear programming, discrete optimization, global optimization, optimization under uncertainty, multi-objective optimization, optimal control and stochastic optimal control;





Includes an extensive bibliography at the end of each chapter and an index;





GAMS files of case studies for Chapters 2, 3, 4, 5, and 7 are linked to http://www.springer.com/math/book/978-0-387-76634-8;





Solutions manual available upon adoptions.

Sommaire:
Preface.- 1. Introduction.- 2. Linear Programming.- 3. Nonlinear Programming.- 4. Discrete Optimization.- 5. Optimization under Uncertainty.- 6. Multi-objective Optimization.- 7. Optimal Control and Dynamic Optimization.- Index.