| Description |
xxviii, 699 pages : illustrations ; 25 cm |
| Series |
Nonconvex optimization and its applications ; v. 45 |
|
Nonconvex optimization and its applications ; v. 45
|
| Contents |
Pt. 1. Global Optimization Algorithms as Decision Procedures, Theoretical Background and Core Univariate Case -- 1. Introduction -- 2. Global Optimization Algorithms as Statistical Decision Procedures - The Information Approach -- 3. Core Global Search Algorithm and Convergence Study -- 4. Global Optimization Methods as Bounding Procedures - The Geometric Approach -- Pt. 2. Generalizations for Parallel Computing, Constrained and Multiple Criteria Problems -- 5. Parallel Global Optimization Algorithms and Evaluation of the Efficiency of Parallelism -- 6. Global Optimization Under Non-Convex Constraints - The Index Approach -- 7. Algorithms for Multiple Criteria Multiextremal Problems -- Pt. 3. Global Optimization in Many Dimensions. Generalizations through Peano Curves -- 8. Peano-Type Space-Filling Curves as Means for Multivariate Problems -- 9. Multidimensional Parallel Algorithms -- 10. Multiple Peano Scannings and Multidimensional Problems |
| Summary |
"This book presents a new approach to global non-convex constrained optimization. Problem dimensionality is reduced via space filling curves. To economize the search constraint is accounted separately (penalties are not employed). The multicriteria case is also considered. All techniques are generalized for (non-redundant) execution on multiprocessor systems." "Audience: Researchers and students working in optimization, applied mathematics, and computer science."--BOOK JACKET |
| Notes |
Includes index |
| Bibliography |
Includes bibliographical references (pages 651-678) and index |
| Subject |
Mathematical optimization.
|
|
Nonconvex programming.
|
| Author |
Sergeyev, Yaroslav D., 1963-
|
| LC no. |
00044375 |
| ISBN |
0792364902 (alk. paper) |
|
