TY - GEN
T1 - Monogamous pair bonding in genetic algorithm
AU - Lim, Ting Yee
AU - Al-Betar, Mohammed Azmi
AU - Khader, Ahamad Tajudin
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/9/10
Y1 - 2015/9/10
N2 - A new variant of the Genetic Algorithm (GA) inspired by monogamy mating system is put forward. The Monogamous Pairs Genetic Algorithm (MopGA) incorporates two important operations: pair bonding and infidelity at a small probability. With pair bonding, parents continue to mate at each iteration until their bond expires. In the meantime, infidelity generates variety and promotes diversity via mating with extrapair. We evaluate the algorithm's performance using various parametrizations and making comparisons to the Standard Genetic Algorithm (SGA) based on the Hierarchical If-and-Only-If (HIFF) and Deceptive (DP) functions. Empirical results show that incorporating pair bonding is a practical move. Improvement in performance in terms of solution quality and computational efforts have been observed for all test problems. Additionally, we also report the effectiveness of MopGA in handling easy and difficult sudoku puzzles.
AB - A new variant of the Genetic Algorithm (GA) inspired by monogamy mating system is put forward. The Monogamous Pairs Genetic Algorithm (MopGA) incorporates two important operations: pair bonding and infidelity at a small probability. With pair bonding, parents continue to mate at each iteration until their bond expires. In the meantime, infidelity generates variety and promotes diversity via mating with extrapair. We evaluate the algorithm's performance using various parametrizations and making comparisons to the Standard Genetic Algorithm (SGA) based on the Hierarchical If-and-Only-If (HIFF) and Deceptive (DP) functions. Empirical results show that incorporating pair bonding is a practical move. Improvement in performance in terms of solution quality and computational efforts have been observed for all test problems. Additionally, we also report the effectiveness of MopGA in handling easy and difficult sudoku puzzles.
UR - https://www.scopus.com/pages/publications/84963622474
U2 - 10.1109/CEC.2015.7256869
DO - 10.1109/CEC.2015.7256869
M3 - Conference contribution
AN - SCOPUS:84963622474
T3 - 2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings
SP - 15
EP - 22
BT - 2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - IEEE Congress on Evolutionary Computation, CEC 2015
Y2 - 25 May 2015 through 28 May 2015
ER -