On the application of natural algorithms to structural design optimization |
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| Affiliation: | 1. Department of Electrical Engineering, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran;2. Department of Electronic Science, University of Pune, Pune, Maharashtra, India;1. Faculty of Civil Engineering, HCMC University of Technology and Education, 1 Vo Van Ngan Street, Thu Duc District, Ho Chi Minh City, Viet Nam;2. Quality Assurance and Testing Center 3, 49 Pasteur Street, District 1, Ho Chi Minh City, Viet Nam;3. School of Civil, Environmental & Architectural Engineering, Korea University, 145 An-Am Ro, Sung-Buk Gu, Seoul 02841, Republic of Korea;4. College of Pipeline and Civil Engineering, China University of Petroleum (East China), No. 66 Changjiang West Rd., Qingdao 266580, PR China;5. Institute of Structural Mechanics, Bauhaus University Weimar, Marienstr. 15, 99425 Weimar, Germany;1. Department of Economic Mathematics, University of Economics and Law, Vietnam National University – Ho Chi Minh City, Vietnam;2. Faculty of Political Science and Pedagogy, University of Physical Education and Sports, Ho Chi Minh City, Vietnam;3. Faculty of Mathematics and Computer Science, University of Science, Vietnam National University – Ho Chi Minh City, Vietnam;4. College of Natural Sciences, Can Tho University, Can Tho City, Vietnam;5. Department of Mathematics Teacher Education, Dong Thap University, Dong Thap Province, Vietnam;6. Fractional Calculus, Optimization and Algebra Research Group, Faculty of Mathematics and Statistics, Ton Duc Thang University, Ho Chi Minh City, Vietnam;1. Virtual Vehicle Research Center, Inffeldgasse 21A, A-8010 Graz, Austria;2. Dipartimento di Ingegneria Meccanica, Politecnico di Milano, Italy;3. Graz University of Technology, Institute of Mechanics, Austria;4. AVL List GmbH, Austria;1. School of Civil & Hydraulic Engineering, Hefei University of Technology, 193 Tunxi Road, Hefei 230009, PR China;2. Department of Civil and Environmental Engineering, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA 15213, USA |
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| Abstract: | Powerful computational methods based on metaphors of ‘urvival of the fittest’ (the genetic algorithm) and human brain activity (the neural network) have made significant progress in engineering where there are needs for search and learning mechanisms. The principal subject of the paper is the ‘genetic algorithm’, a ‘population-based’ method of searching large combinatorial (design) spaces to find the optimum combination of design variables. Attention needs to be given to the form and organization of the algorithm if it is to be applied to large-scale problems. Consideration is given to the development of a space condensation heuristic which progressively reduces the size of the multidimensional space being searched thus leading to a more economical application of the algorithm. The approach to adaptivity of controls and the type of penalty function used for the design constraints are explained. Some results from a study of optimum design of a multistorey frame are included by way of illustration. |
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