Pair Bonds In Genetic Algorithm
Tesis ini membentangkan siasatan komprehensif berasaskan konsep ikatan pasangan (pasangan monogami) yang akan dilaksanakan dalam fasa rekombinasi algoritma genetik (GA). GA merupakan teknik pencarian heuristik berdasarkan prinsip dan mekanisma pilihan semula jadi dan teori "survival of the f...
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| Format: | Thesis |
| Language: | English |
| Published: |
2015
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| Subjects: | |
| Online Access: | http://eprints.usm.my/31889/1/LIM_TING_YEE_%28HJ%29.pdf http://eprints.usm.my/31889/ |
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| Summary: | Tesis ini membentangkan siasatan komprehensif berasaskan konsep ikatan pasangan (pasangan
monogami) yang akan dilaksanakan dalam fasa rekombinasi algoritma genetik (GA).
GA merupakan teknik pencarian heuristik berdasarkan prinsip dan mekanisma pilihan semula
jadi dan teori "survival of the fittest". Biasanya kromosom ibubapa akan dipilih pada setiap
generasi bagi menghasilkan kromosom anak melalui operasi percantuman (crossover) dan mutasi.
Proses ini diulangi sehingga syarat berhenti dipenuhi. Tetapi kadang-kala alam semula
jadi mempamerkan pembentukan hubungan yang berkekalan antara pasangan mengawan. Dalam
masyarakat manusia moden, sesetengah burung, ikan, tikus, dan cicak, ikatan pasangan
merupakan aspek penting dalam tingkah laku sosial mereka. Mereka biasanya mengekalkan
pasangan yang sama sepanjang hidup - monogami sosial. Oleh itu, tesis ini mengkaji kesesuaian
aplikasi ikatan pasangan dalam GA. Dua kaedah GA baru akan dibentangkan: Kaedah
pertama dikenali sebagai Algoritma Genetik Ikatan Monogami (MopGA). Dalam MopGA, kromosom
ibubapa akan berkekalan sehingga beberapa generasi.
This work presents a comprehensive investigation on the concept of pair bonds (monogamous
pairs) for the mating phase of genetic algorithms (GAs). GA is a heuristic search technique
based on the principles and mechanisms of natural selection. Traditionally, parents are
selected at every generation to reproduce offspring through crossover and mutation operations.
The process reiterates until some termination conditions are met. However, nature sometimes
exhibits the formation of enduring relationships between mating partners. In modern human
society, some avian models, fish, rodents, and even lizards, pair bonds are integral aspects
of their social behaviour. These species usually share the same mating partners throughout
their lifetime - socially monogamous. Taking the cue from nature, this thesis studies the feasibilities
of pair bonds in GA. Consequently, two methodologies are proposed: Firstly, in the
Monogamous Pairs Genetic Algorithm (MopGA), parents are bonded and mated consistently
over several predefined generations. Selection of new parents pairs will only take place at the
end of pair bond tenure. Meanwhile, competition occurs between siblings to ensure only the
best offspring are retained. Occasional infidelity generates variety, spreads genetic information
across the population and speeds up convergence. Secondly, to improve the ease-of-use
of MopGA, an adaptive MopGA (AMopGA) is introduced. |
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