Geometry and sizing optimisation of discrete structure using the genetic programming method

This paper presents a structural optimisation method using the genetic programming (GP) technique. This method applied linear GP to derive optimum geometry and sizing of discrete structure from an arbitrary initial design space. The linear GP was used to find out the optimum nodal locations and member sizing of the structure through a linear sequence of programming instructions. The nodal locations and member cross-sectional areas of the structure were used as the design variable for these instructions, with the optimal geometry and sizing obtained by evolving a population of GP individuals satisfying the optimisation design objective. The approach was applied to the benchmark example of ten-bar planar truss for verification. Other truss examples, including 18-bar planar truss and 25-bar space truss, were also used to demonstrate the effectiveness of this method. The optimum results obtained demonstrate the practicability and generality of using the proposed method in geometry and sizing optimisation problems.

[1]  Lucien A. Schmit,et al.  Configuration Optimization of Trusses , 1981 .

[2]  S. Rajeev,et al.  Discrete Optimization of Structures Using Genetic Algorithms , 1992 .

[3]  Chee Kiong Soh,et al.  Genetic programming-based approach for structural optimization , 2000 .

[4]  Chee Kiong Soh,et al.  Fuzzy Controlled Genetic Algorithm Search for Shape Optimization , 1996 .

[5]  U. Kirsch Synthesis of structural geometry using approximation concepts , 1982 .

[6]  Riccardo Poli,et al.  Evolution of Graph-Like Programs with Parallel Distributed Genetic Programming , 1997, ICGA.

[7]  Larry J. Eshelman Proceedings of the Sixth International Conference on Genetic Algorithms : University of Pittsburgh, July 15-19, 1995 , 1995 .

[8]  Samuel L. Lipson,et al.  The complex method applied to optimal truss configuration , 1977 .

[9]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.

[10]  Chee Kiong Soh,et al.  Fuzzy Logic Integrated Genetic Programming for Optimization and Design , 2000 .

[11]  G. N. Vanderplaats,et al.  Configuration Optimization of Trusses Subject to Strength, Displacement and Frequency Constraints , 1987 .

[12]  Wolfgang Banzhaf,et al.  SYSGP - A C++ library of different GP variants , 1998 .

[13]  George I. N. Rozvany,et al.  Optimal Layout of Grillages , 1977 .

[14]  Jamshid Ghaboussi,et al.  Evolution of Optimum Structural Shapes Using Genetic Algorithm , 1998 .

[15]  Garret N. Vanderplaats,et al.  Automated Design of Trusses for Optimum Geometry , 1972 .

[16]  Subramaniam Rajan,et al.  Sizing, Shape, and Topology Design Optimization of Trusses Using Genetic Algorithm , 1995 .

[17]  Mariano Vázquez Espí Discussion: Genetic Algorithms-Based Methodologies for Design Optimization of Trusses , 1998 .

[18]  Vassili Toropov,et al.  APPROXIMATION MODEL BUILDING FOR DESIGN OPTIMIZATION USING GENETIC PROGRAMMING METHODOLOGY , 1998 .

[19]  Jiaping Yang,et al.  Structural Optimization by Genetic Algorithms with Tournament Selection , 1997 .

[20]  Harvey J. Greenberg,et al.  Automatic design of optimal structures , 1964 .

[21]  Wolfgang Banzhaf,et al.  A comparison of linear genetic programming and neural networks in medical data mining , 2001, IEEE Trans. Evol. Comput..

[22]  S Rajeev,et al.  GENETIC ALGORITHMS - BASED METHODOLOGY FOR DESIGN OPTIMIZATION OF TRUSSES , 1997 .

[23]  M. Galante,et al.  GENETIC ALGORITHMS AS AN APPROACH TO OPTIMIZE REAL‐WORLD TRUSSES , 1996 .

[24]  Shyue-Jian Wu,et al.  Integrated discrete and configuration optimization of trusses using genetic algorithms , 1995 .