A smart repair embedded memetic algorithm for 2D shape matching problems |
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| Authors: | Mohammad Sharif Khan Ahmad F Mohamad Ayob Amitay Isaacs Tapabrata Ray |
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| Affiliation: | 1. School of Engineering and Information Technology , University of New South Wales, Australian Defence Force Academy , Canberra , Australia Mohammad.Khan2@student.adfa.edu.au;3. School of Engineering and Information Technology , University of New South Wales, Australian Defence Force Academy , Canberra , Australia;4. Fakulti Pengajian Maritim dan Sains Marin , Universiti Malaysia Terengganu , Terengganu , Malaysia;5. School of Engineering and Information Technology , University of New South Wales, Australian Defence Force Academy , Canberra , Australia |
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| Abstract: | Shape representation plays a major role in any shape optimization exercise. The ability to identify a shape with good performance is dependent on both the flexibility of the shape representation scheme and the efficiency of the optimization algorithm. In this article, a memetic algorithm is presented for 2D shape matching problems. The shape is represented using B-splines, in which the control points representing the shape are repaired and subsequently evolved within the optimization framework. The underlying memetic algorithm is a multi-feature hybrid that combines the strength of a real coded genetic algorithm, differential evolution and a local search. The efficiency of the proposed algorithm is illustrated using three test problems, wherein the shapes were identified using a mere 5000 function evaluations. Extension of the approach to deal with problems of unknown shape complexity is also presented in the article. |
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| Keywords: | shape representation optimization evolutionary algorithm shape matching |
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