TY - GEN
T1 - Empirical study on the effect of population size on differential evolution algorithm
AU - Mallipeddi, R.
AU - Suganthan, P. N.
PY - 2008
Y1 - 2008
N2 - In this paper, we investigate the effect of population size on the quality of solutions and the computational effort required by the Differential evolution (DE) Algorithm. A set of 5 problems chosen from the problem set of CEC 2005 Special Session on Real-Parameter Optimization are used to study the effect of population sizes on the performance of the DE. Results include the effects of various population sizes on the 10 and 30-dimensional versions of each problem for two different mutation strategies. Our study shows a significant influence of the population size on the performance of DE as well as interactions between mutation strategies, population size and dimensionality of the problems.
AB - In this paper, we investigate the effect of population size on the quality of solutions and the computational effort required by the Differential evolution (DE) Algorithm. A set of 5 problems chosen from the problem set of CEC 2005 Special Session on Real-Parameter Optimization are used to study the effect of population sizes on the performance of the DE. Results include the effects of various population sizes on the 10 and 30-dimensional versions of each problem for two different mutation strategies. Our study shows a significant influence of the population size on the performance of DE as well as interactions between mutation strategies, population size and dimensionality of the problems.
UR - https://www.scopus.com/pages/publications/55749093216
U2 - 10.1109/CEC.2008.4631294
DO - 10.1109/CEC.2008.4631294
M3 - Conference contribution
AN - SCOPUS:55749093216
SN - 9781424418237
T3 - 2008 IEEE Congress on Evolutionary Computation, CEC 2008
SP - 3663
EP - 3670
BT - 2008 IEEE Congress on Evolutionary Computation, CEC 2008
T2 - 2008 IEEE Congress on Evolutionary Computation, CEC 2008
Y2 - 1 June 2008 through 6 June 2008
ER -