Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
It is sometimes claimed that genetic algorithms using diploid representations will be more suitable for problems in which the environment changes from time to time, as the additional information stored, in the double chromosome will ensure diversity, which in turn allows the system to respond more quickly and robustly to a change in the fitness function. We have tested various diploid algorithms, with and without mechanisms for dominance change, on non-stationary problems, and conclude that some form of dominance change is essential, as a diploid encoding is not enough in itself to allow flexible response to change. Moreover, a haploid method which randomly mutates chromosomes whose fitness has fallen sharply also performs well on these problems.
Original language | English |
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Title of host publication | Parallel Problem Solving from Nature — PPSN V |
Publisher | Springer |
Pages | 139-148 |
Number of pages | 10 |
Volume | 1498 |
ISBN (Electronic) | 978-3-540-49672-4 |
ISBN (Print) | 978-3-540-65078-2 |
DOIs | |
Publication status | Published - 1998 |
Name | Lecture Notes in Computer Science |
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Publisher | Springer Berlin Heidelberg |
ISSN (Print) | 0302-9743 |
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Research output: Contribution to conference › Abstract › peer-review
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Research output: Contribution to journal › Article › peer-review
Research output: Contribution to journal › Article › peer-review
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
ID: 248684976