- author = "Alan Piszcz and Terence Soule",
- title = "Genetic Programming: Optimal Population Sizes for Varying Complexity Problems",
- booktitle = "GECCO 2006: Proceedings of the 8th annual conference on Genetic and evolutionary computation",
- year = "2006",
- editor = "Maarten Keijzer and Mike Cattolico and Dirk Arnold and Vladan Babovic and Christian Blum and Peter Bosman and Martin V. Butz and Carlos {Coello Coello} and Dipankar Dasgupta and Sevan G. Ficici and James Foster and Arturo Hernandez-Aguirre and Greg Hornby and Hod Lipson and Phil McMinn and Jason Moore and Guenther Raidl and Franz Rothlauf and Conor Ryan and Dirk Thierens",
- volume = "1",
- ISBN = "1-59593-186-4",
- pages = "953--954",
- address = "Seattle, Washington, USA",
-
URL = "
http://gpbib.cs.ucl.ac.uk/gecco2006/docs/p953.pdf",
-
DOI = "
doi:10.1145/1143997.1144166",
- publisher = "ACM Press",
- publisher_address = "New York, NY, 10286-1405, USA",
- month = "8-12 " # jul,
- organisation = "ACM SIGEVO (formerly ISGEC)",
- keywords = "genetic algorithms, genetic programming, binomial-3, MAX binary tree problem, optimal, population sizing, problem difficulty, sizing, Automatic Programming, program synthesis, Algorithms, Performance, Experimentation: Poster",
- size = "2 pages",
- abstract = "The population size in evolutionary computation is a significant parameter affecting computational effort and the ability to successfully evolve solutions. We find that population size sensitivity - how much a genetic program's efficiency varies with population size - is correlated with problem complexity. An analysis of population sizes was conducted using a unimodal, bimodal and a multi-modal problem with varying levels of difficulty. Specifically we show that a unimodal and bimodal and multimodal problems exhibit an increased sensitivity to population size with increasing levels of difficulty. We demonstrate that as problem complexity increases, determination of the optimal population size becomes more difficult. Conversely, the less complex a problem is the more sensitive the genetic program's efficiency is to population size.",
-
notes = "GECCO-2006 A joint meeting of the fifteenth
international conference on genetic algorithms
(ICGA-2006) and the eleventh annual genetic programming
conference (GP-2006).
ACM Order Number 910060",
