Oct 31, 2018 · The performance measure is the error rate for each crossover operator tested. Experiments are performed in two rounds. In the first round, the ...
Nov 1, 2018 · This paper presents comparison of 13 crossover operators on 20 benchmark problems using genetic algorithm. An exhaustive statistical study shows ...
Bibliographic details on Performance Assessment of Thirteen Crossover Operators Using GA.
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The results show significant statistical differences between operators and an overall good performance of uniform, single-point and reduced surrogate crossover.
The performance of Genetic Algorithm (GA) depends on various operators. Crossover operator is one of them. Crossover operators are mainly classified as ...
Missing: Assessment Thirteen
This paper will help researchers in selecting appropriate crossover operator for better results. The paper contains description about classical standard ...
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Taking into account the task specific, each genotype contains the full set of genes. In this case we can get an optimal solution using a crossover operator.
Mar 9, 1999 · In this paper, we deal with promising crossover operators developed in the genetic algorithm (GA) and analyze the performance of these ...
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Aug 16, 2022 · For this type of problem Genetic Algorithm (GA) can be used to get a perfect approximation in a short period. These problems are considered as ...
This paper presents a comparison of 10 crossover oper- ators that are used in genetic algorithms with binary representation. To achieve this, experiments are ...
Missing: Assessment Thirteen