Adaptive mutation methods have ranged from individual gene-based mutations to Gaussian mutation operators based on the mean and the standard deviation of the Gaussian distribution.
Parents are selected for crossover and mutation operators based on crowded tournament selection operator.
The above genetic operators based on evolutionary directions are special for MOPs.
Several researchers obtained various other generalizations of operators based on q-calculus.
Speed-relatedness was assigned to operators based on contributing factors or similar state crash file attributes.
There have been a variety of studies on genetic operators based on evolutionary directions.
In 1989, Razi [5] studied convergence properties of Stancu-Kantorovich operators based on Pólya-Eggenberger distribution.
In this work, an algorithm has been introduced for reverse problem formulations using property operators based on molecular signature descriptors.
A general class of scale-separating operators based on combined multigrid operators is proposed and analyzed in this work.
In this paper, we introduce a bivariate Kantorovich variant of combination of Szász and Chlodowsky operators based on Charlier polynomials.
The approximation properties for these operators based on Korovkin's theorem and some direct theorems were considered [8].
