TY - GEN
T1 - Evolutionary Population Dynamic Mechanisms for the Harmony Search Algorithm
AU - Mirjalili, Seyedeh Zahra
AU - Sajeev, Shelda
AU - Saha, Ratna
AU - Khodadadi, Nima
AU - Mirjalili, Seyed Mohammad
AU - Mirjalili, Seyedali
PY - 2022
Y1 - 2022
N2 - Evolutionary algorithms have been widely adopted in science and industry for optimizing challenging problems mainly due to their black box nature and high local optima avoidance. As popular soft computing techniques, they benefit from several stochastic operators, including but not limited to, selection, recombination, mutation, elitism, population diversity, and population dynamics. Among such operators, some have been extensively used and analyzed in different algorithms, while others are yet to be explored in different algorithms. This motivated our attempts to integrate Evolutionary Population Dynamics (EPD) in the Harmony Search (HS) algorithm. EPD is an evolutionary mechanism that excludes and/or replaces a set of the poor solutions in each generation and prevents them from reducing the quality of other solutions. EPD has been used in three different ways in HS to impact 10%, 30%, or 50% of the population to see its impact on the performance of this algorithm. It was observed that 10% is a reasonable portion of the population in HS to improve its performance on IEEE Congress of Evolutionary computation (CEC) test functions, which effectively mimic challenging real-world optimization problems.
AB - Evolutionary algorithms have been widely adopted in science and industry for optimizing challenging problems mainly due to their black box nature and high local optima avoidance. As popular soft computing techniques, they benefit from several stochastic operators, including but not limited to, selection, recombination, mutation, elitism, population diversity, and population dynamics. Among such operators, some have been extensively used and analyzed in different algorithms, while others are yet to be explored in different algorithms. This motivated our attempts to integrate Evolutionary Population Dynamics (EPD) in the Harmony Search (HS) algorithm. EPD is an evolutionary mechanism that excludes and/or replaces a set of the poor solutions in each generation and prevents them from reducing the quality of other solutions. EPD has been used in three different ways in HS to impact 10%, 30%, or 50% of the population to see its impact on the performance of this algorithm. It was observed that 10% is a reasonable portion of the population in HS to improve its performance on IEEE Congress of Evolutionary computation (CEC) test functions, which effectively mimic challenging real-world optimization problems.
KW - Algorithm
KW - Evolutionary algorithm
KW - Evolutionary operator
KW - Evolutionary Population Dynamics
KW - Harmony Search
KW - Optimization
UR - http://www.scopus.com/inward/record.url?scp=85137571609&partnerID=8YFLogxK
U2 - 10.1007/978-981-19-2948-9_18
DO - 10.1007/978-981-19-2948-9_18
M3 - Conference contribution
AN - SCOPUS:85137571609
SN - 978-981-19-2950-2
SN - 978-981-19-2947-2
T3 - Lecture Notes on Data Engineering and Communications Technologies
SP - 185
EP - 194
BT - Proceedings of 7th International Conference on Harmony Search, Soft Computing and Applications
A2 - Kim, Joong Hoon
A2 - Deep, Kusum
A2 - Geem, Zong Woo
A2 - Sadollah, Ali
A2 - Yadav, Anupam
PB - Springer Singapore
CY - Singapore
ER -