東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Hybrid metaheuristics = powerful too...

Blum, Christian.

FindBook

Google Book

Amazon

博客來

Hybrid metaheuristics = powerful tools for optimization /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Hybrid metaheuristics/ by Christian Blum, Gunther R. Raidl.
其他題名:	powerful tools for optimization /
作者:	Blum, Christian.
其他作者:	Raidl, Gunther R.
出版者:	Cham :Springer International Publishing : : 2016.,
面頁冊數:	xvi, 157 p. :ill., digital ;24 cm.
內容註:	Introduction -- Incomplete Solution Representations and Decoders -- Hybridization Based on Problem Instance Reduction -- Hybridization Based on Large Neighborhood Search -- Making Use of a Parallel, Non-independent, Construction of Solutions Within Metaheuristics -- Hybridization Based on Complete Solution Archives -- Further Hybrids and Conclusions.
Contained By:	Springer eBooks
標題:	Heuristic programming. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-30883-8
ISBN:	9783319308838

Hybrid metaheuristics = powerful tools for optimization /
Blum, Christian.

Hybrid metaheuristicspowerful tools for optimization /[electronic resource] :by Christian Blum, Gunther R. Raidl. - Cham :Springer International Publishing :2016. - xvi, 157 p. :ill., digital ;24 cm. - Artificial intelligence: foundations, theory, and algorithms,2365-3051. - Artificial intelligence: foundations, theory, and algorithms..

Introduction -- Incomplete Solution Representations and Decoders -- Hybridization Based on Problem Instance Reduction -- Hybridization Based on Large Neighborhood Search -- Making Use of a Parallel, Non-independent, Construction of Solutions Within Metaheuristics -- Hybridization Based on Complete Solution Archives -- Further Hybrids and Conclusions.

This book explains the most prominent and some promising new, general techniques that combine metaheuristics with other optimization methods. A first introductory chapter reviews the basic principles of local search, prominent metaheuristics, and tree search, dynamic programming, mixed integer linear programming, and constraint programming for combinatorial optimization purposes. The chapters that follow present five generally applicable hybridization strategies, with exemplary case studies on selected problems: incomplete solution representations and decoders; problem instance reduction; large neighborhood search; parallel non-independent construction of solutions within metaheuristics; and hybridization based on complete solution archives. The authors are among the leading researchers in the hybridization of metaheuristics with other techniques for optimization, and their work reflects the broad shift to problem-oriented rather than algorithm-oriented approaches, enabling faster and more effective implementation in real-life applications. This hybridization is not restricted to different variants of metaheuristics but includes, for example, the combination of mathematical programming, dynamic programming, or constraint programming with metaheuristics, reflecting cross-fertilization in fields such as optimization, algorithmics, mathematical modeling, operations research, statistics, and simulation. The book is a valuable introduction and reference for researchers and graduate students in these domains.

ISBN: 9783319308838

Standard No.: 10.1007/978-3-319-30883-8doiSubjects--Topical Terms:

698997
Heuristic programming.

LC Class. No.: T57.84

Dewey Class. No.: 006.3

Hybrid metaheuristics = powerful tools for optimization /
LDR:02941nmm a2200337 a 4500 001 2037951
003 DE-He213
005 20161021105932.0
006 m d
007 cr nn 008maaau
008 161209s2016 gw s 0 eng d
020 $a 9783319308838 $q (electronic bk.)
020 $a 9783319308821 $q (paper)
024 7 $a 10.1007/978-3-319-30883-8 $2 doi
035 $a 978-3-319-30883-8
040 $a GP $c GP
041 0 $a eng
050 4 $a T57.84
072 7 $a UYQ $2 bicssc
072 7 $a TJFM1 $2 bicssc
072 7 $a COM004000 $2 bisacsh
082 0 4 $a 006.3 $2 23
090 $a T57.84 $b .B658 2016
100 1 $a Blum, Christian. $3 907305
245 1 0 $a Hybrid metaheuristics $h [electronic resource] : $b powerful tools for optimization / $c by Christian Blum, Gunther R. Raidl.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a xvi, 157 p. : $b ill., digital ; $c 24 cm.
490 1 $a Artificial intelligence: foundations, theory, and algorithms, $x 2365-3051
505 0 $a Introduction -- Incomplete Solution Representations and Decoders -- Hybridization Based on Problem Instance Reduction -- Hybridization Based on Large Neighborhood Search -- Making Use of a Parallel, Non-independent, Construction of Solutions Within Metaheuristics -- Hybridization Based on Complete Solution Archives -- Further Hybrids and Conclusions.
520 $a This book explains the most prominent and some promising new, general techniques that combine metaheuristics with other optimization methods. A first introductory chapter reviews the basic principles of local search, prominent metaheuristics, and tree search, dynamic programming, mixed integer linear programming, and constraint programming for combinatorial optimization purposes. The chapters that follow present five generally applicable hybridization strategies, with exemplary case studies on selected problems: incomplete solution representations and decoders; problem instance reduction; large neighborhood search; parallel non-independent construction of solutions within metaheuristics; and hybridization based on complete solution archives. The authors are among the leading researchers in the hybridization of metaheuristics with other techniques for optimization, and their work reflects the broad shift to problem-oriented rather than algorithm-oriented approaches, enabling faster and more effective implementation in real-life applications. This hybridization is not restricted to different variants of metaheuristics but includes, for example, the combination of mathematical programming, dynamic programming, or constraint programming with metaheuristics, reflecting cross-fertilization in fields such as optimization, algorithmics, mathematical modeling, operations research, statistics, and simulation. The book is a valuable introduction and reference for researchers and graduate students in these domains.
650 0 $a Heuristic programming. $3 698997
650 0 $a Mathematical optimization. $3 517763
650 1 4 $a Computer Science. $3 626642
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 890894
650 2 4 $a Theory of Computation. $3 892514
650 2 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Operation Research/Decision Theory. $3 1620900
650 2 4 $a Optimization. $3 891104
700 1 $a Raidl, Gunther R. $3 892758
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Artificial intelligence: foundations, theory, and algorithms. $3 2160111
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-30883-8
950 $a Computer Science (Springer-11645)