Experimental supplements to the theoretical analysis of migration in the island model

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6238 LNCS, Issue PART 1, 2010, Pages 224-233

  Lässig, Jörg ^a   Sudholt, Dirk ^a  

^a INTERNATIONAL COMPUTER SCIENCE INSTITUTE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EMPIRICAL EVIDENCE; EMPIRICAL RESULTS; ISLAND MODEL; MIGRATION TOPOLOGY; NON-TRIVIAL; PARALLEL EVOLUTIONARY ALGORITHMS; RUNNING TIME ANALYSIS; THEORETICAL RESULT;

PROBLEM SOLVING;

STATISTICAL TESTS;

EID: 78149272696     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15844-5_23     Document Type: Conference Paper

References (7)

1. Alba, E.: Parallel evolutionary algorithms can achieve super-linear performance. Information Processing Letters 82(1), 7-13 (2002)
2. He, J., Yao, X.: Analysis of scalable parallel evolutionary algorithms. In: Proceedings of CEC 2006, pp. 120-127 (2006)
3. Cantú-Paz, E., Goldberg, D.E.: On the scalability of parallel genetic algorithms. Evolutionary Computation 7(4), 429-449 (1999)
4. Tomassini, M.: Spatially Structured Evolutionary Algorithms: Artificial Evolution in Space and Time. Springer, Heidelberg (2005)
5. Skolicki, Z., De Jong, K.: The influence of migration sizes and intervals on island models. In: Proceedings of GECCO 2005, pp. 1295-1302. ACM, New York (2005)
6. Lässig, J., Sudholt, D.: The benefit of migration in parallel evolutionary algorithms. In: Proceedings of GECCO 2010, pp. 1105-1112. ACM, New York (2010)
7. Wineberg, M., Christensen, S.: Statistical analysis for evolutionary computation: introduction. In: Companion of GECCO 2009, pp. 2949-2976. ACM, New York (2009)