How crossover helps in Pseudo-Boolean optimization

Genetic and Evolutionary Computation Conference, GECCO'11

Volumn , Issue , 2011, Pages 989-996

  Kötzing, Timo ^a   Sudholt, Dirk ^b   Theile, Madeleine ^c  

^a MAX PLANCK INSTITUTE FOR INFORMATICS   (Germany)

^b UNIVERSITY OF BIRMINGHAM   (United Kingdom)

^c TECHNISCHE UNIVERSITÄT BERLIN   (Germany)

Author keywords

Crossover; Pseudo Boolean optimization; Recombination; Runtime analysis

Indexed keywords

CROSS-OVER PROBABILITY; CROSSOVER; EMPIRICAL RESULTS; MONTE CARLO SIMULATION; POPULATION DIVERSITY; PSEUDO-BOOLEAN OPTIMIZATION; RECOMBINATION; RUN-TIME ANALYSIS; SIMPLE GA; SMALL POPULATION; WORKING PRINCIPLES;

BIOLOGY; BOOLEAN FUNCTIONS; COMPUTER SIMULATION; MATHEMATICAL OPERATORS; MONTE CARLO METHODS; OPTIMIZATION;

GENETIC ALGORITHMS;

EID: 84860407680     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2001576.2001711     Document Type: Conference Paper

References (24)

1. J. Culberson. Genetic invariance: A new paradigm for genetic algorithm design. Technical report, 1992.
2. M. Dietzfelbinger, B. Naudts, C. Van Hoyweghen, and I. Wegener. The analysis of a recombinative hill-climber on H-IFF. IEEE Transactions on Evolutionary Computation, 7(5):417-423, 2003.
3. B. Doerr, E. Happ, and C. Klein. Crossover can provably be useful in evolutionary computation. In Proc. of GECCO '08, pages 539-546. ACM, 2008.
4. B. Doerr, D. Johannsen, T. Kötzing, F. Neumann, and M. Theile. More effective crossover operators for the all-pairs shortest path problem. In Proc. of PPSN '10, pages 184-193. Springer, 2010.
5. B. Doerr and M. Theile. Improved analysis methods for crossover-based algorithms. In Proc. of GECCO '09, pages 247-254. ACM, 2009.
6. S. Droste, T. Jansen, and I. Wegener. On the analysis of the (1+1) evolutionary algorithm. Theoretical Computer Science, 276:51-81, 2002.
7. S. Droste, T. Jansen, and I. Wegener. Upper and lower bounds for randomized search heuristics in black-box optimization. Theory of Computing Systems, 39(4):525-544, 2006. (Pubitemid 43876884)
8. S. Fischer and I. Wegener. The one-dimensional Ising model: Mutation versus recombination. Theoretical Computer Science, 344(2-3):208-225, 2005. (Pubitemid 41550360)
9. T. Friedrich, P. S. Oliveto, D. Sudholt, and C. Witt. Analysis of diversity-preserving mechanisms for global exploration. Evolutionary Computation, 17(4):455-476, 2009.
10. J. He and X. Yao. A study of drift analysis for estimating computation time of evolutionary algorithms. Natural Computing, 3(1):21-35, 2004. (Pubitemid 39127657)
11. C. Horoba and D. Sudholt. Running time analysis of ACO systems for shortest path problems. In Proc. of SLS '09, pages 76-91. Springer, 2009.
12. T. Jansen and I. Wegener. The analysis of evolutionary algorithms - a proof that crossover really can help. Algorithmica, 34(1):47-66, 2002.
13. T. Jansen and I. Wegener. Real royal road functions - where crossover provably is essential. Discrete Applied Mathematics, 149:111-125, 2005. (Pubitemid 41000311)
14. P. K. Lehre and C. Witt. Black box search by unbiased variation. In Proc. of GECCO '10, pages 1441-1448, 2010.
15. A. Moraglio. Convex evolutionary search. In Proc. of FOGA '11, pages 151-162. ACM, 2011.
16. F. Neumann and M. Theile. How crossover speeds up evolutionary algorithms for the multi-criteria all-pairs-shortest-path problem. In Proc. of PPSN '10, pages 667-676. Springer, 2010.
17. F. Neumann and C. Witt. Bioinspired Computation in Combinatorial Optimization - Algorithms and Their Computational Complexity. Springer, 2010.
18. P. S. Oliveto, J. He, and X. Yao. Time complexity of evolutionary algorithms for combinatorial optimization: A decade of results. Int'l Journal of Automation and Computing, 4(3):281-293, 2007. (Pubitemid 47167355)
19. J. N. Richter, A. Wright, and J. Paxton. Ignoble trails - where crossover is provably harmful. In Proc. of PPSN '08, pages 92-101. Springer, 2008.
20. T. Storch and I. Wegener. Real royal road functions for constant population size. Theoretical Computer Science, 320:123-134, 2004.
21. D. Sudholt. Crossover is provably essential for the Ising model on trees. In Proc. of GECCO '05, pages 1161-1167. ACM, 2005. (Pubitemid 43226428)
22. R. A. Watson and T. Jansen. A building-block royal road where crossover is provably essential. In Proc. of GECCO '07, pages 1452-1459. ACM, 2007. (Pubitemid 47291715)
23. I. Wegener. Methods for the analysis of evolutionary algorithms on pseudo-Boolean functions. In R. Sarker, X. Yao, and M. Mohammadian, editors, Evolutionary Optimization, pages 349-369. Kluwer, 2002.
24. A. H. Wright, M. D. Vose, and J. E. Rowe. Implicit parallelism. In Proc. of GECCO '03, pages 1505-1517. Springer, 2003.