A bi-level hierarchical method for shape and member sizing optimization of steel truss structures

This paper describes a new bi-level hierarchical method for optimizing the shape and member sizes of both determinate and indeterminate truss structures. The method utilizes a unique combination of algorithms that are organized hierarchically: the Fully Constrained Design (FCD) method for discrete sizing optimization is nested within SEQOPT, a gradient-based optimization method that operates on continuous shape variables. We benchmarked the method against several existing techniques using numerical examples and found that it compared favorably in terms of solution quality and computational efficiency. We also present a successful industry application of the method to demonstrate its practical benefits.

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

[2]  Niels Leergaard Pedersen,et al.  Optimization of practical trusses with constraints on eigenfrequencies, displacements, stresses, and buckling , 2003 .

[3]  Wolfgang Beitz,et al.  Engineering Design: A Systematic Approach , 1984 .

[4]  O. Hasançebi,et al.  Adaptive evolution strategies in structural optimization: Enhancing their computational performance with applications to large-scale structures , 2008 .

[5]  Andrew Booker,et al.  Design and analysis of computer experiments , 1998 .

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

[7]  A. J. Booker,et al.  A rigorous framework for optimization of expensive functions by surrogates , 1998 .

[8]  G. Vanderplaats,et al.  Method for nonlinear optimization with discrete design variables , 1989 .

[9]  Kristina Shea,et al.  Towards integrated performance-driven generative design tools , 2004 .

[10]  Shahram Pezeshk,et al.  Optimized Design of Two-Dimensional Structures Using a Genetic Algorithm , 1998 .

[11]  O. Hasançebi,et al.  Optimization of truss bridges within a specified design domain using evolution strategies , 2007 .

[12]  G. Vanderplaats,et al.  Approximation method for configuration optimization of trusses , 1990 .

[13]  Min Liu,et al.  Fully Stressed Design of Frame Structures and Multiple Load Paths , 2002 .

[14]  Pruettha Nanakorn,et al.  An adaptive penalty function in genetic algorithms for structural design optimization , 2001 .

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

[16]  E. Salajegheh,et al.  Optimum design of trusses with discrete sizing and shape variables , 1993 .

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

[18]  L. A. Schmit,et al.  Structural synthesis - Its genesis and development , 1981 .

[19]  James O. Malley,et al.  Structural Steel Selection Considerations: A Guide for Students, Educators, Designers, and Builders , 2001 .

[20]  E. Hinton,et al.  Optimization of trusses using genetic algorithms for discrete and continuous variables , 1999 .

[21]  Tomasz Arciszewski,et al.  Emergent Designer: An Integrated Research and Design Support Tool Based on Models of Complex Systems , 2005, J. Inf. Technol. Constr..

[22]  T. Elperin,et al.  Monte Carlo structural optimization in discrete variables with annealing algorithm , 1988 .

[23]  Robert F. Woodbury,et al.  Whither design space? , 2006, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[24]  Uri Kirsch,et al.  Structural Optimization: Fundamentals and Applications , 1993 .

[25]  Abhinav Gupta,et al.  A novel optimization approach for minimum cost design of trusses , 2007 .

[26]  D. Grierson,et al.  Optimal sizing, geometrical and topological design using a genetic algorithm , 1993 .

[27]  B. H. V. Topping,et al.  Shape Optimization of Skeletal Structures: A Review , 1983 .

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

[29]  Nasa,et al.  7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization : a collection of technical papers, September 2-4, 1998/St. Louis, Missouri , 1998 .

[30]  W. M. Jenkins,et al.  Towards structural optimization via the genetic algorithm , 1991 .

[31]  Charles Audet,et al.  A surrogate-model-based method for constrained optimization , 2000 .

[32]  R. Shield,et al.  Optimum design methods for multiple loading , 1963 .

[33]  L. Berke,et al.  Structural optimization using optimality criteria , 1987 .

[34]  Tomasz Arciszewski,et al.  Evolutionary computation and structural design: A survey of the state-of-the-art , 2005 .

[35]  William T. Segui.  LRFD Steel Design , 1994 .

[36]  G. Vanderplaats,et al.  Structural optimization by methods of feasible directions. , 1973 .

[37]  N. S. Khot,et al.  ALGORITHMS BASED ON OPTIMALITY CRITERIA TO DESIGN MINIMUM WEIGHT STRUCTURES , 1981 .

[38]  Pauli Pedersen,et al.  Optimal Joint Positions for Space Trusses , 1973 .

[39]  R. J. Dakin,et al.  A tree-search algorithm for mixed integer programming problems , 1965, Comput. J..

[40]  John Haymaker,et al.  A comparison of multidisciplinary design, analysis and optimization processes in the building construction and aerospace industries , 2007 .

[41]  E. Sandgren,et al.  Nonlinear Integer and Discrete Programming in Mechanical Design Optimization , 1990 .

[42]  Tomasz Arciszewski,et al.  Evolutionary Computation in Structural Design , 2000, Engineering with Computers.

[43]  Garret N. Vanderplaats,et al.  An approximation method for configuration optimization of trusses , 1988 .

[44]  H. Randolph Thomas,et al.  Optimum least-cost design of a truss roof system , 1977 .

[45]  J. A. Bland.  Discrete-variable optimal structural design using tabu search , 1995 .