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Scholars Journal of Engineering and Technology | Volume-4 | Issue-06
A Genetic Algorithm for Solving Multimodal Functions Based on Neighborhood Penalty Function
Nengfa Hu
Published: June 25, 2016 |
139
145
DOI: 10.21276/sjet.2016.4.6.4
Pages: 280-283
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Abstract
By utilizing the neighborhood penalty function and mutation method, the research puts forward a novel
genetic algorithm (GA) by combining global search and local search. Based on the strategy of multiple evolutions, the
algorithm constructs a neighborhood with the result of each evolution as the centre, and then sets a penalty function to
punish individuals in the neighborhood. The experiment proves that the algorithm converges rapidly, shows favorable
global superiority, and is not likely to get trapped in a local optimum. Endowed with these advantages, the algorithm
presents preferable global performance and therefore is universally applicable to multimodal functions with multiple
solutions