國立高雄大學圖資館 |

Language: English

Back

Natural computing for simulation-bas...

Leopold, Nadiia.

Natural computing for simulation-based optimization and beyond

Record Type:	Electronic resources : Monograph/item
Title/Author:	Natural computing for simulation-based optimization and beyondby Silja Meyer-Nieberg, Nadiia Leopold, Tobias Uhlig.
Author:	Meyer-Nieberg, Silja.
other author:	Leopold, Nadiia.
Published:	Cham :Springer International Publishing :2020.
Description:	vii, 60 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Natural computation.
Online resource:	https://doi.org/10.1007/978-3-030-26215-0
ISBN:	9783030262150$q(electronic bk.)

Natural computing for simulation-based optimization and beyond
Meyer-Nieberg, Silja.

Natural computing for simulation-based optimization and beyond[electronic resource] /by Silja Meyer-Nieberg, Nadiia Leopold, Tobias Uhlig. - Cham :Springer International Publishing :2020. - vii, 60 p. :ill. (some col.), digital ;24 cm. - SpringerBriefs in operations research,2195-0482. - SpringerBriefs in operations research..

Chapter 1. Introduction to Simulation-Based Optimization -- Chapter 2. Natural Computing and Optimization -- Chapter 3. Simulation-based Optimization -- Chapter 4 Conclusions.

This SpringerBrief bridges the gap between the areas of simulation studies on the one hand, and optimization with natural computing on the other. Since natural computing methods have been applied with great success in several application areas, a review concerning potential benefits and pitfalls for simulation studies is merited. The brief presents such an overview and combines it with an introduction to natural computing and selected major approaches, as well as with a concise treatment of general simulation-based optimization. As such, it is the first review which covers both the methodological background and recent application cases. The brief is intended to serve two purposes: First, it can be used to gain more information concerning natural computing, its major dialects, and their usage for simulation studies. It also covers the areas of multi-objective optimization and neuroevolution. While the latter is only seldom mentioned in connection with simulation studies, it is a powerful potential technique. Second, the reader is provided with an overview of several areas of simulation-based optimization which range from logistic problems to engineering tasks. Additionally, the brief focuses on the usage of surrogate and meta-models. The brief presents recent application examples.

ISBN: 9783030262150$q(electronic bk.)

Standard No.: 10.1007/978-3-030-26215-0doiSubjects--Topical Terms:

339160
Natural computation.

LC Class. No.: QA76.9.N37 / M49 2020

Dewey Class. No.: 006.38

Natural computing for simulation-based optimization and beyond
LDR:02595nmm a2200349 a 4500 001 577194
003 DE-He213
005 20200214153238.0
006 m d
007 cr nn 008maaau
008 201130s2020 sz s 0 eng d
020 $a 9783030262150$q(electronic bk.)
020 $a 9783030262143$q(paper)
024 7 $a 10.1007/978-3-030-26215-0 $2 doi
035 $a 978-3-030-26215-0
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.N37 $b M49 2020
072 7 $a KJT $2 bicssc
072 7 $a BUS049000 $2 bisacsh
072 7 $a KJT $2 thema
072 7 $a KJMD $2 thema
082 0 4 $a 006.38 $2 23
090 $a QA76.9.N37 $b M613 2020
100 1 $a Meyer-Nieberg, Silja. $3 865493
245 1 0 $a Natural computing for simulation-based optimization and beyond $h [electronic resource] / $c by Silja Meyer-Nieberg, Nadiia Leopold, Tobias Uhlig.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a vii, 60 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a SpringerBriefs in operations research, $x 2195-0482
505 0 $a Chapter 1. Introduction to Simulation-Based Optimization -- Chapter 2. Natural Computing and Optimization -- Chapter 3. Simulation-based Optimization -- Chapter 4 Conclusions.
520 $a This SpringerBrief bridges the gap between the areas of simulation studies on the one hand, and optimization with natural computing on the other. Since natural computing methods have been applied with great success in several application areas, a review concerning potential benefits and pitfalls for simulation studies is merited. The brief presents such an overview and combines it with an introduction to natural computing and selected major approaches, as well as with a concise treatment of general simulation-based optimization. As such, it is the first review which covers both the methodological background and recent application cases. The brief is intended to serve two purposes: First, it can be used to gain more information concerning natural computing, its major dialects, and their usage for simulation studies. It also covers the areas of multi-objective optimization and neuroevolution. While the latter is only seldom mentioned in connection with simulation studies, it is a powerful potential technique. Second, the reader is provided with an overview of several areas of simulation-based optimization which range from logistic problems to engineering tasks. Additionally, the brief focuses on the usage of surrogate and meta-models. The brief presents recent application examples.
650 0 $a Natural computation. $3 339160
650 0 $a Computer simulation. $3 182122
650 0 $a Program transformation (Computer programming) $3 285662
650 1 4 $a Operations Research/Decision Theory. $3 273963
650 2 4 $a Optimization. $3 274084
700 1 $a Leopold, Nadiia. $3 865494
700 1 $a Uhlig, Tobias. $3 865495
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a SpringerBriefs in operations research. $3 680166
856 4 0 $u https://doi.org/10.1007/978-3-030-26215-0
950 $a Business and Management (Springer-41169)