Bioinspired computation in combinatorial optimization: algorithms and their computational complexity

Publication: Research - peer-reviewArticle in proceedings – Annual report year: 2012

Standard

Bioinspired computation in combinatorial optimization: algorithms and their computational complexity. / Neumann, Frank; Witt, Carsten.

Proceedings of the fourteenth international conference on Genetic and evolutionary computation: Companion. Association for Computing Machinery, 2012. p. 1035-1058.

Publication: Research - peer-reviewArticle in proceedings – Annual report year: 2012

Harvard

Neumann, F & Witt, C 2012, 'Bioinspired computation in combinatorial optimization: algorithms and their computational complexity'. in Proceedings of the fourteenth international conference on Genetic and evolutionary computation: Companion. Association for Computing Machinery, pp. 1035-1058., 10.1145/2330784.2330928

APA

Neumann, F., & Witt, C. (2012). Bioinspired computation in combinatorial optimization: algorithms and their computational complexity. In Proceedings of the fourteenth international conference on Genetic and evolutionary computation: Companion. (pp. 1035-1058). Association for Computing Machinery. 10.1145/2330784.2330928

CBE

Neumann F, Witt C. 2012. Bioinspired computation in combinatorial optimization: algorithms and their computational complexity. In Proceedings of the fourteenth international conference on Genetic and evolutionary computation: Companion. Association for Computing Machinery. pp. 1035-1058. Available from: 10.1145/2330784.2330928

MLA

Neumann, Frank and Carsten Witt "Bioinspired computation in combinatorial optimization: algorithms and their computational complexity". Proceedings of the fourteenth international conference on Genetic and evolutionary computation: Companion. Association for Computing Machinery. 2012. 1035-1058. Available: 10.1145/2330784.2330928

Vancouver

Neumann F, Witt C. Bioinspired computation in combinatorial optimization: algorithms and their computational complexity. In Proceedings of the fourteenth international conference on Genetic and evolutionary computation: Companion. Association for Computing Machinery. 2012. p. 1035-1058. Available from: 10.1145/2330784.2330928

Author

Neumann, Frank; Witt, Carsten / Bioinspired computation in combinatorial optimization: algorithms and their computational complexity.

Proceedings of the fourteenth international conference on Genetic and evolutionary computation: Companion. Association for Computing Machinery, 2012. p. 1035-1058.

Publication: Research - peer-reviewArticle in proceedings – Annual report year: 2012

Bibtex

@inbook{9bdb225d6de74613afdc65ddffb088ff,
title = "Bioinspired computation in combinatorial optimization: algorithms and their computational complexity",
publisher = "Association for Computing Machinery",
author = "Frank Neumann and Carsten Witt",
year = "2012",
doi = "10.1145/2330784.2330928",
isbn = "978-1-4503-1178-6",
pages = "1035-1058",
booktitle = "Proceedings of the fourteenth international conference on Genetic and evolutionary computation",

}

RIS

TY - GEN

T1 - Bioinspired computation in combinatorial optimization: algorithms and their computational complexity

A1 - Neumann,Frank

A1 - Witt,Carsten

AU - Neumann,Frank

AU - Witt,Carsten

PB - Association for Computing Machinery

PY - 2012

Y1 - 2012

N2 - Bioinspired computation methods, such as evolutionary algorithms and ant colony optimization, are being applied successfully to complex engineering and combinatorial optimization problems, and it is very important that we understand the computational complexity of these algorithms. This tutorials explains the most important results achieved in this area.<br/><br/>The presenters show how runtime behavior can be analyzed in a rigorous way, in particular for combinatorial optimization. They present well-known problems such as minimum spanning trees, shortest paths, maximum matching, and covering and scheduling problems. Classical single objective optimization is examined first. They then investigate the computational complexity of bioinspired computation applied to multiobjective variants of the considered combinatorial optimization problems, and in particular they show how multiobjective optimization can help to speed up bioinspired computation for single-objective optimization problems.<br/><br/>The tutorial is based on a book written by the authors with the same title. Further information about the book can be found at www.bioinspiredcomputation.com.

AB - Bioinspired computation methods, such as evolutionary algorithms and ant colony optimization, are being applied successfully to complex engineering and combinatorial optimization problems, and it is very important that we understand the computational complexity of these algorithms. This tutorials explains the most important results achieved in this area.<br/><br/>The presenters show how runtime behavior can be analyzed in a rigorous way, in particular for combinatorial optimization. They present well-known problems such as minimum spanning trees, shortest paths, maximum matching, and covering and scheduling problems. Classical single objective optimization is examined first. They then investigate the computational complexity of bioinspired computation applied to multiobjective variants of the considered combinatorial optimization problems, and in particular they show how multiobjective optimization can help to speed up bioinspired computation for single-objective optimization problems.<br/><br/>The tutorial is based on a book written by the authors with the same title. Further information about the book can be found at www.bioinspiredcomputation.com.

U2 - 10.1145/2330784.2330928

DO - 10.1145/2330784.2330928

SN - 978-1-4503-1178-6

BT - Proceedings of the fourteenth international conference on Genetic and evolutionary computation

T2 - Proceedings of the fourteenth international conference on Genetic and evolutionary computation

SP - 1035

EP - 1058

ER -