Global Optimization with Non-Convex Constraints

Sequential and Parallel Algorithms

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May 8, 2020 | History

Global Optimization with Non-Convex Constraints

Sequential and Parallel Algorithms

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.

Publish Date
Publisher
Springer
Pages
732

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Edition Availability
Cover of: Global Optimization with Non-Convex Constraints
Global Optimization with Non-Convex Constraints: Sequential and Parallel Algorithms
Oct 04, 2014, Springer
paperback
Cover of: Global Optimization with Non-Convex Constraints
Cover of: Global Optimization with Non-Convex Constraints

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Edition Notes

Source title: Global Optimization with Non-Convex Constraints: Sequential and Parallel Algorithms

The Physical Object

Format
paperback
Number of pages
732

ID Numbers

Open Library
OL28016213M
ISBN 10
1461546788
ISBN 13
9781461546788

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May 8, 2020 Created by ImportBot Imported from amazon.com record