| Crossover can provably be useful in evolutionary computation |
| Full text |
Pdf
(268 KB)
|
Source
|
Genetic And Evolutionary Computation Conference
archive
Proceedings of the 10th annual conference on Genetic and evolutionary computation
table of contents
Atlanta, GA, USA
SESSION: Evolutionary combinatorial optimization papers
table of contents
Pages 539-546
Year of Publication: 2008
ISBN:978-1-60558-130-9
|
|
Authors
|
|
Benjamin Doerr
|
Max-Planck-Institut für Informatik, Saarbrücken, Germany
|
|
Edda Happ
|
Max-Planck-Institut für Informatik, Saarbrücken, Germany
|
|
Christian Klein
|
Max-Planck-Institut für Informatik, Saarbrücken, Germany
|
|
| Sponsors |
|
| Publisher |
|
| Bibliometrics |
Downloads (6 Weeks): 21, Downloads (12 Months): 85, Citation Count: 6
|
|
|
ABSTRACT
We show that the natural evolutionary algorithm for the all-pairs shortest path problem is significantly faster with a crossover operator than without. This is the first theoretical analysis proving the usefulness of crossover for a non-artificial problem.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
| |
1
|
C. W. Ahn and R. Ramakrishna. A genetic algorithm for shortest path routing problem and the sizing of populations. IEEE Trans. Evolutionary Computation, 6:566--579, 2002.
|
| |
2
|
N. Alon and J. H. Spencer. The Probabilistic Method. Wiley, 2nd edition, 2000.
|
| |
3
|
|
| |
4
|
B. Doerr, E. Happ, and C. Klein. A tight bound for the (11)-EA on the single source shortest path problem. In Proc. of CEC '07, pages 1890--1895. IEEE Press, 2007.
|
| |
5
|
S. Fischer and I. Wegener. The Ising model on the ring: Mutation versus recombination. In Proc. of GECCO '04, volume 3102 of LNCS, pages 1113--1124. Springer, 2004.
|
 |
6
|
|
| |
7
|
|
| |
8
|
|
| |
9
|
|
| |
10
|
J. Inagaki, M. Haseyama, and H. Kitajima. A genetic algorithm for determining multiple routes and its applications. In Proc. of ISCAS '99, pages 137--140. IEEE Press, 1999.
|
| |
11
|
|
| |
12
|
|
| |
13
|
|
 |
14
|
|
| |
15
|
S. Kirkpatrick, D. Gelatt Jr., and M. P. Vecchi. Optimization by simulated annealing. Science, 220:671--680, 1983.
|
| |
16
|
|
| |
17
|
S. Liang, A. N. Zincir-Heywood, and M. I. Heywood. Adding more intelligence to the network routing problem: AntNet and Ga-agents. Appl. Soft Comput., 6:244--257, 2006.
|
| |
18
|
|
| |
19
|
N. Metropolis, A. Rosenbluth, M. Rosenbluth, A. Teller, and E. Teller. Equations of state calculations by fast computing machines. J. Chemical Physics, 21:1087--1091, 1953.
|
| |
20
|
|
 |
21
|
Yuval Rabani , Yuri Rabinovich , Alistair Sinclair, A computational view of population genetics, Proceedings of the twenty-seventh annual ACM symposium on Theory of computing, p.83-92, May 29-June 01, 1995, Las Vegas, Nevada, United States
[doi> 10.1145/225058.225088]
|
| |
22
|
Y. Rabinovich and A. Wigderson. An analysis of a simple genetic algorithm. In Proc. of ICGA '94, pages 215--221, 1991.
|
| |
23
|
|
| |
24
|
J. Scharnow, K. Tinnefeld, and I. Wegener. The analysis of evolutionary algorithms on sorting and shortest paths problems. J. Math. Model. Algorithms, 3:349--366, 2004.
|
| |
25
|
|
 |
26
|
|
 |
27
|
|
| |
28
|
I. Wegener. Simulated annealing beats metropolis in combinatorial optimization. In Proc. of ICALP '05, volume 3580 of LNCS, pages 589--601. Springer, 2005.
|
| |
29
|
I. Wegener and T. Jansen. The analysis of evolutionary algorithms -- a proof that crossover really can help. Algorithmica, 34:47--66, 2002.
|
CITED BY 6
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Benjamin Doerr , Anton Eremeev , Christian Horoba , Frank Neumann , Madeleine Theile, Evolutionary algorithms and dynamic programming, Proceedings of the 11th Annual conference on Genetic and evolutionary computation, July 08-12, 2009, Montreal, Québec, Canada
|
|
|
|
|