The N-queens problem was used specifically to test the accuracy of the new adaptive mutation rate since a GA implementing a constant mutation rate does not have 100% accuracy in the N-queens problem.
Contrarily, taking into consideration the weakness of existing greedy strategies, [16] introduced a new differential evolution (DE) algorithm, named JADE, to improve optimization performance by implementing a new mutation strategy "DE/current-to-pbest" with optional external archive and updating control parameters in an adaptive manner.
This study also compares a GA implementing an adaptive mutation operator with other well-known search algorithms, such as the Nelder-Mead method, hill climbing technique, and random search.
We developed and implemented an optimized mutation profiling platform ("OncoMap") to interrogate ∼400 mutations in 33 known oncogenes and tumor suppressors, many of which are known to predict response or resistance to targeted therapies.
Wiesner et al. observed that bacterial expression of EphB2 (but not EphA4) resulted in toxicity, and thus implemented an inactivating mutation of the putative catalytic base to generate recombinant kinase in E. coli [ 32].
To implement a maximum number of mutations per cell, the summations in eqns (4) and (5) begin at p = i−4, q = j−4, etc.
To determine whether spindly HA phylogenies, co-circulation of antigenic variants, and high annual attack rates indeed come out of a model that incorporates deleterious mutations, we implemented a phylodynamic model that simulates the occurrence of both non-antigenic (largely deleterious) mutations and antigenic mutations ('Materials and methods').
To achieve this we first implemented a rich family of microsatellite mutation models and related components in the software package BEAST.
To confirm whether or not the properties can be used as criteria for distinguishing LoF and GoF mutations, we implemented a classification technique using the support vector machine, random forest, and linear logistic regression methods with 50 data sets which contain equal numbers of LoF and GoF mutations to avoid bias.
If implementing one mutation operator results in an infeasible solution, that solution will be eliminated.
