@Article{iasc.2020.013926,
AUTHOR = {Fu-I Chou, Wen-Hsien Ho, Chiu-Hung Chen},
TITLE = {Niche Genetic Algorithm for Solving Multiplicity Problems in Genetic Association Studies},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {26},
YEAR = {2020},
NUMBER = {3},
PAGES = {501--512},
URL = {http://www.techscience.com/iasc/v26n3/40009},
ISSN = {2326-005X},
ABSTRACT = {This paper proposes a novel genetic algorithm (GA) that embeds a niche 
competition strategy (NCS) in the evolutionary flow to solve the combinational 
optimization problems that involve multiple loci in the search space. Unlike 
other niche-information based algorithms, the proposed NCSGA does not need 
prior knowledge to design niche parameters in the niching phase. To verify the 
solution capability of the new method, benchmark studies on both the travelling 
salesman problem (TSP) and the airline recovery scheduling problem were first 
made. Then, the proposed method was used to solve single nucleotide 
polymorphism (SNP) barcodes generation problems in a genetic association 
study. Experiments showed that the proposed NCS-based solver substantially 
improves solution quality by maintaining multiple optima.},
DOI = {10.32604/iasc.2020.013926}
}