Saving Effort in Parallel GP by Means of Plagues

Fernández, Francisco V.; Martín, Adanay

doi:10.1007/978-3-540-24650-3_25

Cited by 6 publications

(1 citation statement)

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“…In the former case, examples include early work by Koza (1992), who proposed and editing operator for tree simplification. Others have proposed operators that work at the population level, such a selection strategy that eliminates larger trees (Fernández and Martín 2004;Luke and Panait 2006). A more recent example is the prune and plant method, an elaborate mutation operator inspired from agricultural practices (Alfaro-Cid et al 2009), which is similar to other specially designed mutation operators, such as hoist and shrink (Kinnear 1993;Angeline 1997).…”

Section: Bloat Control Methodsmentioning

confidence: 99%

Genetic programming with one-point crossover and subtree mutation for effective problem solving and bloat control

Trujillo

2011

Soft Comput

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Genetic programming (GP) is one of the most widely used paradigms of evolutionary computation due to its ability to automatically synthesize computer programs and mathematical expressions. However, because GP uses a variable length representation, the individuals within the evolving population tend to grow rapidly without a corresponding return in fitness improvement, a phenomenon known as bloat. In this paper, we present a simple bloat control strategy for standard tree-based GP that achieves a one order of magnitude reduction in bloat when compared with standard GP on benchmark tests, and practically eliminates bloat on two real-world problems. Our proposal is to substitute standard subtree crossover with the onepoint crossover (OPX) developed by Poli and Langdon (Second online world conference on soft computing in engineering design and manufacturing, Springer, Berlin (1997)), while maintaining all other GP aspects standard, particularly subtree mutation. OPX was proposed for theoretical purposes related to GP schema theorems, however since it curtails exploration during the search it has never achieved widespread use. In our results, on the other hand, we are able to show that OPX can indeed perform an effective search if it is coupled with subtree mutation, thus combining the bloat control capabilities of OPX with the exploration provided by standard mutation.

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