TY - GEN
T1 - Improved Multi-operator Differential Evolution Algorithm for Solving Unconstrained Problems
AU - Sallam, Karam M.
AU - Elsayed, Saber M.
AU - Chakrabortty, Ripon K.
AU - Ryan, Michael J.
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/7
Y1 - 2020/7
N2 - In recent years, several multi-method and multi-operator-based algorithms have been proposed for solving optimization problems. Generally, their performance is better than other algorithms that based on a single operator and/or algorithm. However, they do not perform consistently well over all the problems tested in the literature. In this paper, we propose an improved optimization algorithm that uses the benefits of multiple differential evolution operators, with more emphasis placed on the best-performing operator. The performance of the proposed algorithm is tested by solving 10 problems with 5, 10, 15 and 20 dimensions taken from CEC2020 competition on single objective bound constrained optimization, with its results outperforming both single operator-based and different state-of-the-art algorithms.
AB - In recent years, several multi-method and multi-operator-based algorithms have been proposed for solving optimization problems. Generally, their performance is better than other algorithms that based on a single operator and/or algorithm. However, they do not perform consistently well over all the problems tested in the literature. In this paper, we propose an improved optimization algorithm that uses the benefits of multiple differential evolution operators, with more emphasis placed on the best-performing operator. The performance of the proposed algorithm is tested by solving 10 problems with 5, 10, 15 and 20 dimensions taken from CEC2020 competition on single objective bound constrained optimization, with its results outperforming both single operator-based and different state-of-the-art algorithms.
KW - adaptive operator selection
KW - differential evolution
KW - evolutionary algorithms
KW - unconstrained optimization
UR - http://www.scopus.com/inward/record.url?scp=85092064722&partnerID=8YFLogxK
U2 - 10.1109/CEC48606.2020.9185577
DO - 10.1109/CEC48606.2020.9185577
M3 - Conference contribution
AN - SCOPUS:85092064722
SN - 9781728169309
T3 - 2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings
SP - 1
EP - 8
BT - 2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings
A2 - Jin, Yaochu
PB - IEEE, Institute of Electrical and Electronics Engineers
CY - United States
T2 - 2020 IEEE Congress on Evolutionary Computation, CEC 2020
Y2 - 19 July 2020 through 24 July 2020
ER -