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The μ-GA is one of the improved form of GAs, to reduce iteration and computing resources by using small populations.
Micro-Genetic Algorithm (μ-GA) is one of the improved forms of Genetic Algorithm (GA), which has been used to find an optimum solution, and to reduce iteration and computing resources by using small populations.
These results show that our proposed approach performs the heuristic search efficiently by using small populations.
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Genetic fitness optimization using small populations or small population updates across generations generally suffers from randomly diverging evolutions.
The clinical pharmacologist, working with the basic pharmacologist can play a major role in aiding target identification and by developing trial designs using small patient populations, mitigating the need for full Phase III studies to test the hypothesis.
For example, in our previous study of epistasis in SUA using small isolated populations genotyped by chips with ∼300 000 SNPs, interactions involving SLC2A9 were detected but could not be robustly replicated (25).
Furthermore, we design a source-tree-based routing algorithm and build the shortest-path multicast tree to minimize delay time by using a small population size in the genetic algorithm.
Results were primary maintained when using smaller random populations.
ChangeEverything is also using small incentives (beyond the goals themselves) to promote population of the site.
This is true of all types of drugs: Old drugs that are used by small populations are vulnerable to price hikes.
Recent studies evaluating the discriminative power of VNTR typing have produced conflicting results that were generated by using convenience samples (small populations with low diversity or populations confined to a single geographic setting).
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