Non-Convex Multi-Objective Optimization /
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 trad...
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Main Authors: | |
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Corporate Authors: | |
Group Author: | ; |
Published: |
Springer International Publishing : Imprint: Springer,
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Publisher Address: | Cham : |
Publication Dates: | 2017. |
Literature type: | eBook |
Language: | English |
Series: |
Springer Optimization and Its Applications,
123 |
Subjects: | |
Online Access: |
http://dx.doi.org/10.1007/978-3-319-61007-8 |
Summary: |
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 a |
Carrier Form: | 1 online resource(XII,192pages): illustrations. |
ISBN: | 9783319610078 |
Index Number: | QA402 |
CLC: | O224 |
Contents: | 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. |