Paper Info
Title
Stud krill herd algorithm
Abstract
Recently, Gandomi and Alavi proposed a meta-heuristic optimization algorithm, called Krill Herd (KH), for global optimization [Gandomi AH, Alavi AH. Krill Herd: A New Bio-Inspired Optimization Algorithm. Communications in Nonlinear Science and Numerical Simulation, 17(12), 4831-4845, 2012.]. This paper represents an optimization method to global optimization using a novel variant of KH. This method is called the Stud Krill Herd (SKH). Similar to genetic reproduction mechanisms added to KH method, an updated genetic reproduction schemes, called stud selection and crossover (SSC) operator, is introduced into the KH during the krill updating process dealing with numerical optimization problems. The introduced SSC operator is originated from original Stud genetic algorithm. In SSC operator, the best krill, the Stud, provides its optimal information for all the other individuals in the population using general genetic operators instead of stochastic selection. This approach appears to be well capable of solving various functions. Several problems are used to test the SKH method. In addition, the influence of the different crossover types on convergence and performance is carefully studied. Experimental results indicate an instructive addition to the portfolio of swarm intelligence techniques.
Year
DOI
Venue
2014
10.1016/j.neucom.2013.08.031
Neurocomputing
Keywords
DocType
Volume
krill herd,kh method,skh method,ssc operator,numerical optimization problem,meta-heuristic optimization algorithm,global optimization,genetic reproduction mechanism,optimization method,general genetic operator,stud krill herd algorithm
Journal
128,
ISSN
Citations 
PageRank 
0925-2312
70
1.84
References 
Authors
24
3
Name
Order
Citations
PageRank
Gai-Ge Wang1125148.96
Amir Hossein Gandomi21836110.25
Amir Hossein Alavi3101645.59