Non-Convex Multi-Objective Optimization

Häftad, Engelska, 2018

Av Panos M. Pardalos, Antanas Žilinskas, Julius Žilinskas, Antanas Zilinskas, Julius Zilinskas, Antanas ilinskas, Antanas ¿Ilinskas, Julius ¿Ilinskas

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Recent results on non-convex multi-objective optimization problems and methods are presented in this book, with particular attention to expensive black-box objective functions.

Produktinformation

Utgivningsdatum2018-06-15
Mått155 x 235 x 12 mm
Vikt318 g
FormatHäftad
SpråkEngelska
SerieSpringer Optimization and Its Applications
Antal sidor192
FörlagSpringer International Publishing AG
ISBN9783319869810

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1. Definitions and Examples.- 2. Scalarization.- 3. Approximation and Complexity.- 4. A Brief Review of Non-Convex Single-Objective Optimization.- 5. Multi-Objective Branch and Bound.- 6. Worst-Case Optimal Algorithms.- 7. Statistical Models Based Algorithms.- 8. Probabilistic Bounds in Multi-Objective Optimization.- 9. Visualization of a Set of Pareto Optimal Decisions.- 10. Multi-Objective Optimization Aided Visualization of Business Process Diagrams. –References.- Index.

“Readers will definitely enjoy this book, because all surveyed topics are rigorously exposed. Moreover, since the main prerequisites are provided, the book is essentially self-contained and easy to read. The authors have also included many illustrative pictures that ensure a good understanding of technical concepts and results. … this book is an excellent reference for researchers and graduate students in both pure and applied mathematics, as well as other disciplines.” (Nicolae Popovici, Mathematical Reviews, August, 2018)