TY - GEN
T1 - Comparison of parameter-setting-free and self-adaptive harmony search
AU - Choi, Young Hwan
AU - Eghdami, Sajjad
AU - Ngo, Thi Thuy
AU - Chaurasia, Sachchida Nand
AU - Kim, Joong Hoon
N1 - Funding Information:
This work was supported by a grant from The National Research Foundation (NRF) of Korea, funded by the Korean government (MSIP) (No. 2016R1A2A1A05005306).
Funding Information:
Acknowledgements This work was supported by a grant from The National Research Foundation (NRF) of Korea, funded by the Korean government (MSIP) (No. 2016R1A2A1A05005306).
Publisher Copyright:
© Springer Nature Singapore Pte Ltd. 2019.
PY - 2019
Y1 - 2019
N2 - This study compares the performance of all parameter-setting-free and self-adaptive harmony search algorithms proposed in the previous studies, which do not ask for the user to set the algorithm parameter values. Those algorithms are parameter-setting-free harmony search, Almost-parameter-free harmony search, novel self-adaptive harmony search, self-adaptive global-based harmony search algorithm, parameter adaptive harmony search, and adaptive harmony search, each of which has a distinctively different mechanism to adaptively control the parameters over iterations. Conventional mathematical benchmark problems of various dimensions and characteristics and water distribution network design problems are used for the comparison. The best, worst, and average values of final solutions are used as performance indices. Computational results show that the performance of each algorithm has a different performance indicator depending on the characteristics of optimization problems such as search space size. Conclusions derived in this study are expected to be beneficial to future research works on the development of a new optimization algorithm with adaptive parameter control. It can be considered to improve the algorithm performance based on the problem’s characteristic in a much simpler way.
AB - This study compares the performance of all parameter-setting-free and self-adaptive harmony search algorithms proposed in the previous studies, which do not ask for the user to set the algorithm parameter values. Those algorithms are parameter-setting-free harmony search, Almost-parameter-free harmony search, novel self-adaptive harmony search, self-adaptive global-based harmony search algorithm, parameter adaptive harmony search, and adaptive harmony search, each of which has a distinctively different mechanism to adaptively control the parameters over iterations. Conventional mathematical benchmark problems of various dimensions and characteristics and water distribution network design problems are used for the comparison. The best, worst, and average values of final solutions are used as performance indices. Computational results show that the performance of each algorithm has a different performance indicator depending on the characteristics of optimization problems such as search space size. Conclusions derived in this study are expected to be beneficial to future research works on the development of a new optimization algorithm with adaptive parameter control. It can be considered to improve the algorithm performance based on the problem’s characteristic in a much simpler way.
KW - Harmony search
KW - Parameter-setting-free
KW - Self-adaptive
UR - http://www.scopus.com/inward/record.url?scp=85053264442&partnerID=8YFLogxK
U2 - 10.1007/978-981-13-0761-4_11
DO - 10.1007/978-981-13-0761-4_11
M3 - Conference contribution
AN - SCOPUS:85053264442
SN - 9789811307607
T3 - Advances in Intelligent Systems and Computing
SP - 105
EP - 112
BT - Harmony Search and Nature Inspired Optimization Algorithms - Theory and Applications, ICHSA 2018
A2 - Bansal, Jagdish Chand
A2 - Kim, Joong Hoon
A2 - Yadav, Anupam
A2 - Deep, Kusum
A2 - Yadav, Neha
PB - Springer Verlag
T2 - 4th International Conference on Harmony Search, Soft Computing and Applications, ICHSA 2018
Y2 - 7 February 2018 through 9 February 2018
ER -