@Article{2019.100000085,
AUTHOR = {Hui Zhi, Sanyang Liu},
TITLE = {A Hybrid GABC-GA Algorithm for Mechanical Design Optimization  Problems},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {25},
YEAR = {2019},
NUMBER = {4},
PAGES = {815--825},
URL = {http://www.techscience.com/iasc/v25n4/39713},
ISSN = {2326-005X},
ABSTRACT = {In this paper, we proposed a hybrid algorithm, which is embedding the genetic 
operators in the global-best-guided artificial bee colony algorithms called GABCGA to solve the nonlinear design optimization problems. The genetic algorithm 
has no memory function and good at find global optimization with large 
probability, but the artificial bee colony algorithm not have selection, crossover 
and mutation operator and most significant at local search. The hybrid 
algorithm balances the exploration and exploitation ability further by combining 
the advantages of both. The experimental results of five engineering 
optimization and comparisons with existing approaches show that the proposed 
approach is outperforms to those typical approaches in terms of the quality of 
the results solutions in most cases.},
DOI = {10.31209/2019.100000085}
}