Optimization of curved roof surface design using GA

Purpose – Due to the increasing complexity of curved roof surface design and the inadequate optimisation algorithms in design software, the optimisation of curved roof surface design needs to be studied further. The purpose of this paper is to develop an alternative approach to improve the efficiency and effectiveness of curved roof surface design of buildings.Design/methodology/approach – To achieve the purpose, an optimisation method/tool is developed through reviewing the application of CATIA and integrating genetic algorithm with CATIA; and the effectiveness to perform the GA‐based optimisation method is demonstrated by using a real‐life case study. Furthermore, a comparison among different optimisation algorithms currently available in the CATIA system is conducted.Findings – Through the case study and the comparison, it is found that the GA‐based method can improve the performance of optimisation for curved roof surface design in the CATIA system; however, further research work is required for the b...

[1]  Sushil J. Louis,et al.  Genetic algorithms as a computational tool for design , 1993 .

[2]  J. Krottmaier Optimizing Engineering Designs , 1993 .

[3]  Ghassan Aouad,et al.  A Generic Guide to the Design and Construction: Process Protocol , 1998 .

[4]  H. Adeli,et al.  Concurrent genetic algorithms for optimization of large structures , 1994 .

[5]  Oded Maimon,et al.  A Mathematical Theory of Design: Foundations, Algorithms and Applications , 1998 .

[6]  H. P. Schwefel,et al.  Numerische Optimierung von Computermodellen mittels der Evo-lutionsstrategie , 1977 .

[7]  Peter J. Bentley,et al.  Evolutionary Design By Computers , 1999 .

[8]  Riaz Mussa,et al.  Curve and surface optimization within the CAD/CAM environment , 2002 .

[9]  J. Poon,et al.  Co-evolution of the fitness function and design solution for design exploration , 1995, Proceedings of 1995 IEEE International Conference on Evolutionary Computation.

[10]  Rajkumar Roy,et al.  Evolutionary computing in manufacturing industry: an overview of recent applications , 2005, Appl. Soft Comput..

[11]  W. Vent,et al.  Rechenberg, Ingo, Evolutionsstrategie — Optimierung technischer Systeme nach Prinzipien der biologischen Evolution. 170 S. mit 36 Abb. Frommann‐Holzboog‐Verlag. Stuttgart 1973. Broschiert , 1975 .

[12]  I. C. Parmee Adaptive Computing in Design and Manufacture , 1998 .

[13]  Moncef Krarti,et al.  Genetic-algorithm based approach to optimize building envelope design for residential buildings , 2010 .

[14]  S. Pourzeynali,et al.  Multi-objective optimization of seismically isolated high-rise building structures using genetic algorithms , 2008 .

[15]  Michel Grédiac,et al.  Combining a finite element programme and a genetic algorithm to optimize composite structures with variable thickness , 2008 .

[16]  Sudhanshu K. Mishra Repulsive Particle Swarm Method on Some Difficult Test Problems of Global Optimization , 2006 .

[17]  Donald E. Grierson Conceptual Design Using Emergent Computing Techniques , 1996 .

[18]  Ingo Rechenberg,et al.  Evolutionsstrategie : Optimierung technischer Systeme nach Prinzipien der biologischen Evolution , 1973 .

[19]  John Christopher Miles,et al.  The conceptual design of commercial buildings using a genetic algorithm , 2001 .

[20]  Dennis R. Shelden,et al.  A Parametric Strategy for Freeform Glass Structures Using Quadrilateral Planar Facets , 2004, ACADIA proceedings.

[21]  Sudhanshu K. Mishra Global Optimization By Particle Swarm Method: A Fortran Program , 2006 .

[22]  T.S. Perry Dennis Shelden: turning dreams into reality , 2004, IEEE Spectrum.

[23]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[24]  Bruce Lindsey Digital Gehry: Material Resistance, Digital Construction , 2001 .

[25]  H. Adeli,et al.  Integrated Genetic Algorithm for Optimization of Space Structures , 1993 .

[26]  H. Adeli,et al.  Augmented Lagrangian genetic algorithm for structural optimization , 1994 .

[27]  Ian C. Parmee,et al.  Evolutionary and adaptive computing in engineering design , 2001 .

[28]  Peter J. Bentley,et al.  Conceptual Evolutionary Design by a Genetic Algorithm , 1997 .

[29]  Jin Cheng,et al.  Reliability analysis of structures using artificial neural network based genetic algorithms , 2008 .

[30]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[31]  Thomas Bäck,et al.  An Overview of Evolutionary Algorithms for Parameter Optimization , 1993, Evolutionary Computation.

[32]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[33]  Tom Remillard,et al.  Finished With a Flourish , 2004 .

[34]  J. D. Mathews,et al.  Conceptual Building Design—Evolutionary Approach , 2003 .

[35]  D. Barral,et al.  An evolutionary simulated annealing algorithm for optimizing robotic task point ordering , 1999, Proceedings of the 1999 IEEE International Symposium on Assembly and Task Planning (ISATP'99) (Cat. No.99TH8470).

[36]  Arturo Jiménez-Gutiérrez,et al.  Use of genetic algorithms for the optimal design of shell-and-tube heat exchangers , 2009 .