Abstract
The reliance of Evolutionary Algorithms on haploid genotypes has proved a difficult area for non-stationary function optimization. While it is generally accepted that various approaches involving diploidy can better cope with these kinds of problems, none of these paradigms have gained wide acceptance in the GA community. We describe Shades, a new haploid system which uses Polygenic Inheritance. Polygenic inheritance differs from most implementations of GAs in that several genes contribute to each phenotypic trait. A Knapsack non-stationary function optimization problems from the literature is described, and it is shown how Shades outperforms diploidy for this task.
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Ryan, C., Collins, J.J., Howard, D. (2011). Optimizing for Change through Shades. In: Lee, G., Howard, D., Ślęzak, D. (eds) Convergence and Hybrid Information Technology. ICHIT 2011. Lecture Notes in Computer Science, vol 6935. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24082-9_33
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DOI: https://doi.org/10.1007/978-3-642-24082-9_33
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