A hybrid imperialist competitive ant colony algorithm for optimum geometry design of frame structures

This paper describes new optimization strategy that offers significant improvements in performance over existing methods for geometry design of frame structures. In this study, an imperialist competitive algorithm (ICA) and ant colony optimization (ACO) are combined to reach to an efficient algorithm, called Imperialist Competitive Ant Colony Optimization (ICACO). The ICACO applies the ICA for global optimization and the ACO for local search. The results of optimal geometry for three benchmark examples of frame structures, demonstrate the effectiveness and robustness of the new method presented in this work. The results indicate that the new technique has a powerful search strategies due to the modifications made in search module of ICACO. Higher rate of convergence is the superiority of the presented algorithm in comparison with the conventional mathematical methods and non hybrid heuristic methods such as ICA and particle swarm optimization (PSO).

[1]  Mehmet Polat Saka,et al.  Optimum design of cellular beams using harmony search and particle swarm optimizers , 2011 .

[2]  Siamak Talatahari,et al.  Optimum design of skeletal structures using imperialist competitive algorithm , 2010 .

[3]  Guan-Chun Luh,et al.  Optimal design of truss structures using ant algorithm , 2008 .

[4]  Liyong Tong,et al.  Improved genetic algorithm for design optimization of truss structures with sizing, shape and topology variables , 2005 .

[5]  Ardeshir Bahreininejad,et al.  Water cycle algorithm - A novel metaheuristic optimization method for solving constrained engineering optimization problems , 2012 .

[6]  Fuat Erbatur,et al.  Layout optimisation of trusses using simulated annealing , 2002 .

[7]  Ardeshir Bahreininejad,et al.  Mine blast algorithm for optimization of truss structures with discrete variables , 2012 .

[8]  Siamak Talatahari,et al.  A hybrid CSS and PSO algorithm for optimal design of structures , 2012 .

[9]  R. Haftka,et al.  Review of options for structural design sensitivity analysis. Part 1: Linear systems , 2005 .

[10]  A. Kaveh,et al.  Sizing, geometry and topology optimization of trusses via force method and genetic algorithm , 2008 .

[11]  D. Wang,et al.  Optimal shape design of a frame structure for minimization of maximum bending moment , 2007 .

[12]  P. Pedersen On optimal shapes in materials and structures , 2000 .

[13]  Weihong Zhang,et al.  Truss shape optimization with multiple displacement constraints , 2002 .

[14]  Siamak Talatahari,et al.  Geometry and topology optimization of geodesic domes using charged system search , 2011 .

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

[16]  Victor Pereyra,et al.  Optimal design of steel frame structures , 2002 .

[17]  Guan-Chun Luh,et al.  Optimal design of truss-structures using particle swarm optimization , 2011 .

[18]  Siamak Talatahari,et al.  Particle swarm optimizer, ant colony strategy and harmony search scheme hybridized for optimization of truss structures , 2009 .

[19]  Caro Lucas,et al.  Colonial competitive algorithm: A novel approach for PID controller design in MIMO distillation column process , 2008, Int. J. Intell. Comput. Cybern..