Reliability-Based Optimal Design of Truss Structures Using Particle Swarm Optimization

In this work, the particle swarm optimization method is employed for the reliability-based optimal design of statically determinate truss structures. Particle swarm optimization is inspired by the social behavior of flocks (swarms) of birds and insects (particles). Every particle's position represents a specific design. The algorithm searches the design space by adjusting the trajectories of the particles that comprise the swarm. These particles are attracted toward the positions of both their personal best solution and the best solution of the swarm in a stochastic manner. In typical structural optimization problems, safety is dealt with in a yes/no manner fulfilling the set of requirements imposed by codes of practice. Considering uncertainty for the problem parameters offers a measure to quantify safety. This measure provides a rational basis for the estimation of the reliability of the components and of the entire system. Incorporating the reliability into the structural optimization framework one can seek a reliability-based optimal design. For the problems examined herein, the reliability indexes of the structural elements are obtained from analytical expressions. The structure is subsequently analyzed as a series system of correlated elements and the Ditlevsen bounds are used for the calculation of its reliability index. The uncertain-random parameters considered in this work are the load, the yield-critical stress; and the cross sections of the elements. The considered design variables of the optimization problem are the cross-sectional areas of the groups, which control the size of the truss, and the heights and lengths that control the shape of the truss. The results of the optimization are presented for a 25-bar truss and a 30-bar arch and the robustness of the optimization scheme is discussed.

[1]  Maurice Clerc Binary Particle Swarm Optimisers: toolbox, derivations, and mathematical insights , 2005 .

[2]  George G. Dimopoulos,et al.  Mixed-variable engineering optimization based on evolutionary and social metaphors , 2007 .

[3]  Andries Petrus Engelbrecht,et al.  Investigating binary PSO parameter influence on the knights cover problem , 2005, 2005 IEEE Congress on Evolutionary Computation.

[4]  Eckart Zitzler,et al.  Evolutionary algorithms for multiobjective optimization: methods and applications , 1999 .

[5]  Ioan Cristian Trelea,et al.  The particle swarm optimization algorithm: convergence analysis and parameter selection , 2003, Inf. Process. Lett..

[6]  C. S. Krishnamoorthy,et al.  System Reliability-Based Configuration Optimization of Trusses , 2001 .

[7]  V. K. Koumousis,et al.  Identification of Bouc-Wen hysteretic systems by a hybrid evolutionary algorithm , 2008 .

[8]  Ajith Abraham,et al.  Chaotic dynamic characteristics in swarm intelligence , 2007, Appl. Soft Comput..

[9]  Hong Zhang,et al.  Permutation-Based Particle Swarm Optimization for Resource-Constrained Project Scheduling , 2006 .

[10]  Palle Thoft-Christensen,et al.  Structural Reliability Theory and Its Applications , 1982 .

[11]  Charles Elegbede,et al.  Structural reliability assessment based on particles swarm optimization , 2005 .

[12]  Kyung K. Choi,et al.  A new response surface methodology for reliability-based design optimization , 2004 .

[13]  Konstantinos E. Parsopoulos,et al.  MULTIOBJECTIVE OPTIMIZATION USING PARALLEL VECTOR EVALUATED PARTICLE SWARM OPTIMIZATION , 2003 .

[14]  Reinhard Männer,et al.  Towards an Optimal Mutation Probability for Genetic Algorithms , 1990, PPSN.

[15]  Armen Der Kiureghian,et al.  Optimal design with probabilistic objective and constraints , 2006 .

[16]  Y. K. Wen,et al.  Minimum lifecycle cost design under multiple hazards , 2001, Reliab. Eng. Syst. Saf..

[17]  M. Janga Reddy,et al.  Multipurpose Reservoir Operation Using Particle Swarm Optimization , 2007 .

[18]  Yue Shi,et al.  A modified particle swarm optimizer , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[19]  Rodrigo Salgado,et al.  Assessment of Variable Uncertainties for Reliability-Based Design of Foundations , 2006 .

[20]  E. Polak,et al.  Reliability-Based Optimal Design of Series Structural Systems , 2001 .

[21]  Shahram Pezeshk,et al.  Probabilistic Performance-Based Optimal Design of Steel Moment-Resisting Frames. I: Formulation , 2007 .

[22]  Y. K. Wen,et al.  Reliability and performance-based design☆ , 2001 .

[23]  Albert A. Groenwold,et al.  Sizing design of truss structures using particle swarms , 2003 .

[24]  I-Tung Yang,et al.  Using elitist particle swarm optimization to facilitate bicriterion time-cost trade-off analysis , 2007 .

[25]  Yukio Kosugi,et al.  Particle Swarms for Feature Extraction of Hyperspectral Data , 2007, IEICE Trans. Inf. Syst..

[26]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[27]  B J Fregly,et al.  Parallel global optimization with the particle swarm algorithm , 2004, International journal for numerical methods in engineering.

[28]  Russell C. Eberhart,et al.  A discrete binary version of the particle swarm algorithm , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[29]  V. K. Koumousis,et al.  Genetic Algorithms in Competitive Environments , 2003 .

[30]  Jaroslaw Sobieszczanski-Sobieski,et al.  Multidisciplinary optimization of a transport aircraft wing using particle swarm optimization , 2002 .

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

[32]  P. Fourie,et al.  The particle swarm optimization algorithm in size and shape optimization , 2002 .

[33]  Yin Chuan,et al.  A Branch and Bound-PSO Hybrid Algorithm for Solving Integer Separable Concave Programming Problems 1 , 2007 .

[34]  David De Leon,et al.  Determination of optimal target reliabilities for design and upgrading of structures , 1997 .

[35]  Y. K. Wen,et al.  Reliability and performance-based design § , 2002 .

[36]  David G. Elms,et al.  Achieving structural safety: theoretical considerations , 1999 .

[37]  K Natarajan,et al.  Reliability based optimization of transmission line towers , 1993 .

[38]  Sankaran Mahadevan,et al.  Design Optimization With System-Level Reliability Constraints , 2008 .

[39]  Palle Thoft-Christensen,et al.  Application of Structural Systems Reliability Theory , 1986 .

[40]  V. K. Koumousis,et al.  RELIABILITY BASED OPTIMAL DESIGN OF STRUCTURES USING COMPETITIVE GENETIC ALGORITHMS , 2004 .

[41]  Yuhui Shi,et al.  Particle swarm optimization: developments, applications and resources , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[42]  Mark M. Millonas,et al.  Swarms, Phase Transitions, and Collective Intelligence , 1993, adap-org/9306002.

[43]  Maurice Clerc,et al.  The particle swarm - explosion, stability, and convergence in a multidimensional complex space , 2002, IEEE Trans. Evol. Comput..