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Population-based approaches to the r...

Ratajczak-Ropel, Ewa.

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Population-based approaches to the resource constrained and discrete continuous scheduling

Record Type:	Electronic resources : Monograph/item
Title/Author:	Population-based approaches to the resource constrained and discrete continuous scheduling/ by Ewa Ratajczak-Ropel, Aleksander Skakovski.
Author:	Ratajczak-Ropel, Ewa.
other author:	Skakovski, Aleksander.
Published:	Cham :Springer International Publishing : : 2018.,
Description:	xviii, 236 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Scheduling - Data processing. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-62893-6
ISBN:	9783319628936

Population-based approaches to the resource constrained and discrete continuous scheduling
Ratajczak-Ropel, Ewa.

Population-based approaches to the resource constrained and discrete continuous scheduling[electronic resource] /by Ewa Ratajczak-Ropel, Aleksander Skakovski. - Cham :Springer International Publishing :2018. - xviii, 236 p. :ill., digital ;24 cm. - Studies in systems, decision and control,v.1082198-4182 ;. - Studies in systems, decision and control ;v.108..

This book addresses two of the most difficult and computationally intractable classes of problems: discrete resource constrained scheduling, and discrete-continuous scheduling. The first part of the book discusses problems belonging to the first class, while the second part deals with problems belonging to the second class. Both parts together offer valuable insights into the possibility of implementing modern techniques and tools with a view to obtaining high-quality solutions to practical and, at the same time, computationally difficult problems. It offers a valuable source of information for practitioners dealing with the real-world scheduling problems in industry, management and administration. The authors have been working on the respective problems for the last decade, gaining scientific recognition through publications and active participation in the international scientific conferences, and their results are obtained using population-based methods. Dr E. Ratajczk-Ropel explores multiple agent and A-Team concepts, while Dr A. Skakovski focuses on evolutionary algorithms with a particular focus on the population learning paradigm.

ISBN: 9783319628936

Standard No.: 10.1007/978-3-319-62893-6doiSubjects--Topical Terms:

2196468
Scheduling
--Data processing.

LC Class. No.: TS157.5

Dewey Class. No.: 658.53

Population-based approaches to the resource constrained and discrete continuous scheduling
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245 1 0 $a Population-based approaches to the resource constrained and discrete continuous scheduling $h [electronic resource] / $c by Ewa Ratajczak-Ropel, Aleksander Skakovski.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2018.
300 $a xviii, 236 p. : $b ill., digital ; $c 24 cm.
490 1 $a Studies in systems, decision and control, $x 2198-4182 ; $v v.108
520 $a This book addresses two of the most difficult and computationally intractable classes of problems: discrete resource constrained scheduling, and discrete-continuous scheduling. The first part of the book discusses problems belonging to the first class, while the second part deals with problems belonging to the second class. Both parts together offer valuable insights into the possibility of implementing modern techniques and tools with a view to obtaining high-quality solutions to practical and, at the same time, computationally difficult problems. It offers a valuable source of information for practitioners dealing with the real-world scheduling problems in industry, management and administration. The authors have been working on the respective problems for the last decade, gaining scientific recognition through publications and active participation in the international scientific conferences, and their results are obtained using population-based methods. Dr E. Ratajczk-Ropel explores multiple agent and A-Team concepts, while Dr A. Skakovski focuses on evolutionary algorithms with a particular focus on the population learning paradigm.
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