Non-Convex Multi-Objective Optimization

1. Auflage 2017
ISBN: 978-3-319-61005-4
Verlag: Springer International Publishing

Buch, Englisch, Band 123, 192 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 4321 g

Reihe: Springer Optimization and Its Applications

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. Multi-objective optimization methods facilitate designers, engineers, and researchers to make decisions on appropriate trade-offs between various conflicting goals. A variety of deterministic and stochastic multi-objective optimization methods are developed in this book. Beginning with basic concepts and a review of non-convex single-objective optimization problems; this book moves on to cover multi-objective branch and bound algorithms, worst-case optimal algorithms (for Lipschitz functions and bi-objective problems), statistical models based algorithms, and probabilistic branch and bound approach. Detailed descriptions of new algorithms for non-convex multi-objective optimization, their theoretical substantiation, and examples for practical applications to the cell formation problem in manufacturing engineering, the process design in chemical engineering, and business process management are included to aide researchers and graduate students in mathematics, computer science, engineering, economics, and business management.

Zielgruppe

Research

Autoren/Hrsg.

Pardalos, Panos M.

¿Ilinskas, Julius

Žilinskas, Antanas

Fachgebiete

• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Numerische Mathematik
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Optimierung
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Mathematische Modellierung
• Mathematik | Informatik EDV | Informatik Informatik Mathematik für Informatiker

Inhaltsverzeichnis

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.