This book presents an overview of archiving strategies developed over the last years by the authors that deal with suitable approximations of the sets of optimal and nearly optimal solutions of multi-objective optimization problems by means of stochastic search algorithms. All presented archivers are analyzed with respect to the approximation qualities of the limit archives that they generate and the upper bounds of the archive sizes. The convergence analysis will be done using a very broad framework that involves all ...
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This book presents an overview of archiving strategies developed over the last years by the authors that deal with suitable approximations of the sets of optimal and nearly optimal solutions of multi-objective optimization problems by means of stochastic search algorithms. All presented archivers are analyzed with respect to the approximation qualities of the limit archives that they generate and the upper bounds of the archive sizes. The convergence analysis will be done using a very broad framework that involves all existing stochastic search algorithms and that will only use minimal assumptions on the process to generate new candidate solutions. All of the presented archivers can effortlessly be coupled with any set-based multi-objective search algorithm such as multi-objective evolutionary algorithms, and the resulting hybrid method takes over the convergence properties of the chosen archiver. This book hence targets at all algorithm designers and practitioners in the fieldof multi-objective optimization.
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Add this copy of Archiving Strategies for Evolutionary Multi-objective to cart. $150.29, new condition, Sold by Ingram Customer Returns Center rated 5.0 out of 5 stars, ships from NV, USA, published 2022 by Springer Nature Switzerland AG.
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Seller's Description:
New. Print on demand Contains: Illustrations, black & white, Illustrations, color. Studies in Computational Intelligence . XIII, 234 p. 130 illus., 44 illus. in color. Intended for professional and scholarly audience.
Add this copy of Archiving Strategies for Evolutionary Multi-Objective to cart. $150.29, new condition, Sold by Ingram Customer Returns Center rated 5.0 out of 5 stars, ships from NV, USA, published 2021 by Springer.
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New. Print on demand Sewn binding. Cloth over boards. 234 p. Contains: Unspecified, Illustrations, black & white, Illustrations, color. Studies in Computational Intelligence, 938.
Add this copy of Archiving Strategies for Evolutionary Multi-objective to cart. $173.27, new condition, Sold by Ria Christie Books rated 4.0 out of 5 stars, ships from Uxbridge, MIDDLESEX, UNITED KINGDOM, published 2022 by Springer Nature Switzerland AG.
Choose your shipping method in Checkout. Costs may vary based on destination.
Seller's Description:
New. Contains: Illustrations, black & white, Illustrations, color. Studies in Computational Intelligence . XIII, 234 p. 130 illus., 44 illus. in color. Intended for professional and scholarly audience.
Add this copy of Archiving Strategies for Evolutionary Multi-Objective to cart. $173.27, new condition, Sold by Ria Christie Books rated 4.0 out of 5 stars, ships from Uxbridge, MIDDLESEX, UNITED KINGDOM, published 2021 by Springer.
