文章基本信息

标题：Bio-Inspired Metaheuristic Methods for Fitting Points in CAGD
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作者：Angel Cobo ; Akemi Gálvez ; Jaime Puig-Pey 等
期刊名称：International Journal of Computer Information Systems and Industrial Management Applications
印刷版ISSN：2150-7988
电子版ISSN：2150-7988
出版年度：2009
卷号：1
页码：36-47
出版社：Machine Intelligence Research Labs (MIR Labs)
摘要：This paper deals with a classical optimizationproblem, fitting 3D data points by means of curve andsurface models used in Computer-Aided Geometric Design(CAGD). Our approach is based on the idea of combiningtraditional techniques, namely best approximationby least-squares, with Genetic Algorithms (GA) andParticle Swarm Optimization (PSO), both based on bioinspiredprocedures emerging from the artificial intelligenceworld. In this work, we focus on fitting pointsthrough free-form parametric curves and surfaces. Thisissue plays an important role in real problems such asconstruction of car bodies, ship hulls, airplane fuselage,and other free-form objects. A typical example comesfrom reverse engineering where free-form curves andsurfaces are extracted from clouds of data points. Theperformance of the proposed methods is analyzed by usingsome examples of B´ezier curves and surfaces.