Nonstationary function optimization using genetic algorithm with dominance and diploidy
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
A New Diploid Scheme and Dominance Change Mechanism for Non-Stationary Function Optimization
Proceedings of the 6th International Conference on Genetic Algorithms
A Comparison of Dominance Mechanisms and Simple Mutation on Non-stationary Problems
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Polygenic Inheritance - A Haploid Scheme that Can Outperform Diploidy
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Non-stationary function optimization using polygenic inheritance
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
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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.