A tree-structured covalent-bond-driven molecular memetic algorithm for optimization of ring-deficient molecules

Ellabaan, Mostafa Mostafa Hashim; Handoko, Stephanus Daniel; Ong, Yew-Soon; Kwoh, Chee-Keong; Bahnassy, S. A.; Elassawy, F. M.; Man, Heng‐Ye

doi:10.1016/j.camwa.2012.02.055

Cited by 8 publications

(1 citation statement)

References 41 publications

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“…Chapters 4 and 5 to efficiently deal with covalently-bonded molecular systems. The extended form of the framework is donated as chemical bond-embedded memetic computational methodology (MMC)[116]. In MMC, tree-based chromosome representation is developed based on knowledge about the molecule structure, as details in Section 7.1.1, where information regarding atoms and bonds of the molecule are extracted and maintained in a tree structure for the whole process of evolution.…”

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Multi-modal memetic framework for locating saddle points, with application to biomolecular systems : water clusters and ring-deficient covalently-bonded small molecules

Ellabaan¹

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His sincere encouragements during my indecisive moment and inspirational insight into the many aspects of my research direction have faithfully guided me throughout my research work. Without Professor Ong's guidance, the fruitful achievement of this project will never be possible. I would also like to thank my friends for their encouragements and the staffs at Emerging research Lab (ER Lab) and Center of computational intelligence (C2I) for their technical supports. Last but not the least, special thanks to my parents, wishing God blessing to cover them, for their constant support, understanding and love, until their last breaths.

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Multi-modal memetic framework for locating saddle points, with application to biomolecular systems : water clusters and ring-deficient covalently-bonded small molecules

Ellabaan¹

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Memetic Algorithms: A Contemporary Introduction

Cotta

Gallardo

Mathieson

et al. 2016

Wiley Encyclopedia of Electrical and Electronics Engineering

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Memetic algorithms (MAs) constitute a search and optimization paradigm based on the orchestrated interplay between global and local search components, and have the exploitation of specific problem knowledge as one of their central tenets. MAs can take different forms although a classical incarnation involves the integration of independent search processes within a population‐based optimization approach. We discuss this basic structure as well as several of the issues arising in the design process. This paves the way for providing a glimpse of some algorithmic extensions of this basic scheme. After providing an overview of the numerous practical applications of MAs, we close this article with some current perspectives of these techniques.

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