etc. Handbook of Test Problems in Local and Global Optimization

Christodoulos A. Floudas, Pãnos M. Pardalos, Claire S. Adjiman, William R. Esposito, Zeynep H. Gümüş, Stephen T. Harding, John L. Klepeis, Clifford A. Meyer, Carl A. Schweiger. — Kluwer, 1999. — 447 p. — ISBN 0-7923-5801-5.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 importance for academic and industrial researchers interested in algorithmic and software development. It is remarkable that even though nonconvex models dominate all the important application areas in engineering and applied sciences, there is only a limited class 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 class of applications that arise in several branches of engineering and applied science.Introduction
Quadratic Programming Problems
Quadratically Constrained Problems
Univariate Polynomial Problems
Bilinear Problems
Biconvex and (D.C.) Problems
Generalized Geometric Programming
Twice Continuously Differentiable NLP Problems
Bilevel Programming Problems
Complementarity Problems
Semidefinite Programming Problems
Mixed-Integer Nonlinear Problems
Combinatorial Optimization Problems
Nonlinear Systems of Equations
Dynamic Optimization Problems