Initialization methods for large scale global optimization

Borhan Kazimipour, Xiaodong Li, A. K. Qin
2013 2013 IEEE Congress on Evolutionary Computation  
Several population initialization methods for evolutionary algorithms (EAs) have been proposed previously. This paper categorizes the most well-known initialization methods and studies the effect of them on large scale global optimization problems. Experimental results indicate that the optimization of large scale problems using EAs is more sensitive to the initial population than optimizing lower dimensional problems. Statistical analysis of results show that basic random number generators,
more » ... ch are the most commonly used method for population initialization in EAs, lead to the inferior performance. Furthermore, our study shows, regardless of the size of the initial population, choosing a proper initialization method is vital for solving large scale problems.
doi:10.1109/cec.2013.6557902 dblp:conf/cec/KazimipourLQ13 fatcat:sg2ohtalufco3aoh3kfrez3co4