Julius ilinskas's Books

Multidimensional Data Visualization

Methods and Applications

By: Gintautas Dzemyda,Olga Kurasova,Julius Žilinskas

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Multidimensional Data Visualization

Methods and Applications

By: Gintautas Dzemyda,Olga Kurasova,Julius Žilinskas

This book highlights recent developments in multidimensional data visualization, presenting both new methods and modifications on classic techniques. Throughout the book, various applications of multidimensional data visualization are presented including its uses in social sciences (economy, education, politics, psychology), environmetrics, and medicine (ophthalmology, sport medicine, pharmacology, sleep medicine). The book provides recent research results in optimization-based visualization. Evolutionary algorithms and a two-level optimization method, based on combinatorial optimization and quadratic programming, are analyzed in detail. The performance of these algorithms and the development of parallel versions are discussed. The utilization of new visualization techniques to improve the capabilies of artificial neural networks (self-organizing maps, feed-forward networks) is also discussed. The book includes over 100 detailed images presenting examples of the many different visualization techniques that the book presents. This book is intended for scientists and researchers in any field of study where complex and multidimensional data must be represented visually.

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Page Count

262

Publisher

Springer Science & Business Media

Published Date

ISBN 10

1441902368

ISBN 13

9781441902368

Non-Convex Multi-Objective Optimization

By: Panos M. Pardalos,Antanas Žilinskas,Julius Žilinskas

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Non-Convex Multi-Objective Optimization

By: Panos M. Pardalos,Antanas Žilinskas,Julius Žilinskas

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.

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Page Count

196

Publisher

Springer

Published Date

ISBN 10

3319610074

ISBN 13

9783319610078

Simplicial Global Optimization

By: Remigijus Paulavičius,Julius Žilinskas

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Simplicial Global Optimization

By: Remigijus Paulavičius,Julius Žilinskas

Simplicial Global Optimization is centered on deterministic covering methods partitioning feasible region by simplices. This book looks into the advantages of simplicial partitioning in global optimization through applications where the search space may be significantly reduced while taking into account symmetries of the objective function by setting linear inequality constraints that are managed by initial partitioning. The authors provide an extensive experimental investigation and illustrates the impact of various bounds, types of subdivision, strategies of candidate selection on the performance of algorithms. A comparison of various Lipschitz bounds over simplices and an extension of Lipschitz global optimization with-out the Lipschitz constant to the case of simplicial partitioning is also depicted in this text. Applications benefiting from simplicial partitioning are examined in detail such as nonlinear least squares regression and pile placement optimization in grillage-type foundations. Researchers and engineers will benefit from simplicial partitioning algorithms such as Lipschitz branch and bound, Lipschitz optimization without the Lipschitz constant, heuristic partitioning presented. This book will leave readers inspired to develop simplicial versions of other algorithms for global optimization and even use other non-rectangular partitions for special applications.

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Page Count

146

Publisher

Springer Science & Business Media

Published Date

ISBN 10

1461490936

ISBN 13

9781461490937

Book's by Julius ilinskas

Multidimensional Data Visualization

Multidimensional Data Visualization

Non-Convex Multi-Objective Optimization

Non-Convex Multi-Objective Optimization

Simplicial Global Optimization

Simplicial Global Optimization

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