Monogamous pair bonding in genetic algorithm

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...

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Bibliographic Details
Main Authors: Ting Yee Lim, Al-Betar, Mohammed Azmi, Khader, Ahamad Tajudin
Format: Conference Proceeding
Language:English
Subjects:
Bonding
Convergence
Genetic algorithms
Genetics
Next generation networking
Sociology
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Summary: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.
ISSN:1089-778X
1941-0026
DOI:10.1109/CEC.2015.7256869