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Algorithm Portfolios(Paperback / softback)
Advances, Applications, and Challenges
Published:
25/03/2021
This book covers algorithm portfolios, multi-method schemes that harness optimization algorithms into a joint framework to solve optimization problems.
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£54.99 |
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£48.12
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From Approximate Variation to Pointwise Selection Principles(Paperback / softback)
Published:
23/10/2021
The new notion of approximate variation contains more information about the bounded variation functional and has the following features: the infimum in the definition of approximate variation is not...
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Krasnosel''skii-Mann Iterative Method(Paperback / softback)
Recent Progress and Applications
Published:
21/03/2022
This brief explores the Krasnosel''skii-Man (KM) iterative method, which has been extensively employed to find fixed points of nonlinear methods.
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Optimization in Banach Spaces(Paperback / softback)
Published:
30/09/2022
The book is devoted to the study of constrained minimization problems on closed and convex sets in Banach spaces with a Frechet differentiable objective function.
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Derivative-free DIRECT-type Global Optimization(Paperback / softback)
Applications and Software
Published:
28/11/2023
Lastly, the authors demonstrate the performance of the algorithms for solving a wide range of global optimization problems with various constraints ranging from a few to hundreds of variables.Additi...
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£34.99
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Krasnoselskii-Mann Method for Common Fixed Point Problems(Paperback / softback)
Published:
25/03/2025
This book delves into the intricate world of fixed point theory, focusing on the Krasnoselskii-Mann method to tackle common fixed point problems within a finite family of quasi-nonexpansive mappings...
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Optimal Social Influence(Paperback / softback)
Published:
30/01/2020
The main topics covered in this book are: chrematistics of social networks, modeling of social influence propagation, popular research problems in social influence analysis such as influence maximiz...
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Projected Subgradient Algorithm in Convex Optimization(Paperback / softback)
Published:
26/11/2020
The discussion takes into consideration the fact that for every algorithm its iteration consists of several steps and that computational errors for different steps are different, in general.
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