Techno Press
Techno Press

Structural Engineering and Mechanics   Volume 61, Number 3, February10 2017, pages 359-370
DOI: http://dx.doi.org/10.12989/sem.2017.61.3.359
 
An integrated particle swarm optimizer for optimization of truss structures with discrete variables
Ali Mortazavi, Vedat Togan and Ayhan Nuhoglu

 
Abstract     [Full Text]
    This study presents a particle swarm optimization algorithm integrated with weighted particle concept and improved fly-back technique. The rationale behind this integration is to utilize the affirmative properties of these new terms to improve the search capability of the standard particle swarm optimizer. Improved fly-back technique introduced in this study can be a proper alternative for widely used penalty functions to handle existing constraints. This technique emphasizes the role of the weighted particle on escaping from trapping into local optimum(s) by utilizing a recursive procedure. On the other hand, it guaranties the feasibility of the final solution by rejecting infeasible solutions throughout the optimization process. Additionally, in contrast with penalty method, the improved fly-back technique does not contain any adjustable terms, thus it does not inflict any extra ad hoc parameters to the main optimizer algorithm. The improved fly-back approach, as independent unit, can easily be integrated with other optimizers to handle the constraints. Consequently, to evaluate the performance of the proposed method on solving the truss weight minimization problems with discrete variables, several benchmark examples taken from the technical literature are examined using the presented method. The results obtained are comparatively reported through proper graphs and tables. Based on the results acquired in this study, it can be stated that the proposed method (integrated particle swarm optimizer, iPSO) is competitive with other metaheuristic algorithms in solving this class of truss optimization problems.
 
Key Words
    optimization; truss structures; particle swarm optimization, weighted particle, constraint handling
 
Address
Ali Mortazavi and Ayhan Nuhoglu : Department of Civil Engineering, Ege University, 35100 İzmir, Turkey
Vedat Togan : Department of Civil Engineering, Karadeniz Technical University, 61080 Trabzon, Turkey
 

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