Non-Convex Multi-Objective Optimization

Panos M. Pardalos, Antanas Žilinskas, Julius Žilinskas (Autoren)

Buch | Hardcover

XII, 192 Seiten

2017 | 1st ed. 2017
Springer International Publishing (Verlag)
978-3-319-61005-4 (ISBN)

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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. 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.

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)

“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)

Erscheinungsdatum	19.08.2017
Reihe/Serie	Springer Optimization and Its Applications
Zusatzinfo	XII, 192 p. 18 illus., 4 illus. in color.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Gewicht	463 g
Themenwelt	Informatik ► Theorie / Studium ► Algorithmen
	Mathematik / Informatik ► Mathematik ► Analysis
	Mathematik / Informatik ► Mathematik ► Angewandte Mathematik
Schlagworte	algorithms • applications in engineering • Binary-Linear Model • Branch-and-Bound approach • continuous problems • Lipschitz optimization • Mathematical Applications in Computer Science • Mathematical Modelling • Mathematics • mathematics and statistics • Multidimensional Bi-Objective Lipschitz Optimizati • Multidimensional Bi-Objective Lipschitz Optimization • non-convex multi-objective optimization • Normal Boundary Intersection • Numerical analysis • Optimal Algorithms for Lipschitz Functions • Optimal Passive Algorithm • Optimal Sequential Algorithm • Optimization • Pareto Frontier • Pareto Optimal Decisions • Pareto Sets • randomized algorithms • Scalarization • Software and Applications • Statistical Models for Global Optimization • Tchebycheff Method • Trisection of a Hyper-rectangle
ISBN-10	3-319-61005-8 / 3319610058
ISBN-13	978-3-319-61005-4 / 9783319610054
Zustand	Neuware