Handbook of Test Problems in Local and Global Optimization

Christodoulos A. Floudas

ISBN 10: 1441948120 / ISBN 13: 9781441948120

Editore: Springer US, 2010

Riguardo questo articolo

Druck auf Anfrage Neuware - Printed after ordering - Significant research activities have taken place in the areas of local and global optimization in the last two decades. Many new theoretical, computational, algorithmic, and software contributions have resulted. It has been realized that despite these numerous contributions, there does not exist a systematic forum for thorough experimental computational testing and evaluation of the proposed optimization algorithms and their implementations. Well-designed nonconvex optimization test problems are of major impor tance for academic and industrial researchers interested in algorithmic and software development. It is remarkable that eventhough nonconvex models dominate all the important application areas in engineering and applied sci ences, there is only a limited dass of reported representative test problems. This book reflects our long term efforts in designing a benchmark database and it is motivated primarily from the need for nonconvex optimization test problems. The present collection of benchmarks indudes test problems from literature studies and a large dass of applications that arise in several branches of engineering and applied science.

Codice articolo 9781441948120

Dati bibliografici

• Titolo: Handbook of Test Problems in Local and Global Optimization
• Editore: Springer US
• Data di pubblicazione: 2010
• Lingua: Inglese
• ISBN 10: 1441948120
• ISBN 13: 9781441948120
• Rilegatura: Taschenbuch
• Condizione: Neu

Descrizione articolo

Riassunto

This collection of challenging and well-designed test problems arising in literature studies also contains a wide spectrum of applications, including pooling/blending operations, heat exchanger network synthesis, homogeneous azeotropic separation, and dynamic optimization and optimal control problems.

Contenuti

Preface. 1. Introduction. 2. Quadratic Programming Problems. 3. Quadratically Constrained Problems. 4. Univariate Polynomial Problems. 5. Bilinear Problems. 6. Biconvex and (D.C.) Problems. 7. Generalized Geometric Programming. 8. Twice Continuously Differentiable NLPs. 9. Bilevel Programming Problems. 10. Complementarity Problems. 11. Semidefinite Programming Problems. 12. Mixed-Integer Nonlinear Problems. 13. Combinatorial Optimization Problems. 14. Nonlinear Systems of Equations. 15. Dynamic Optimization Problems.