A reformulation of the ant colony optimization algorithm for large scale structural optimization

Date

2011-01-01

Author

Hasançebi, Oğuzhan
Saka, M.p.

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This study intends to improve performance of ant colony optimization (ACO) method for structural optimization problems particularly with many design variables or when design variables are chosen from large discrete sets. The algorithm developed with ACO method employs the so-called pheromone scaling approach to overcome entrapment of the search in a poor local optimum and thus to recover efficiency of the method for large-scale optimization problems. Besides, a new formulation is proposed for the local update parameter in the algorithm. The efficacy of the proposed algorithm is quantified using two numerical design examples chosen from practical size optimum design of steel structures. The results obtained with the proposed algorithm are compared with those of other methods, such as particle swarm optimization (PSO), harmony search optimization (HSO) and genetic algorithms (GAs). The design problems are formulated according to the provisions of ASD-AISC (Allowable Stress Design Code of American Institute of Steel Institution).

Subject Keywords

Ant colony optimization method, Discrete optimum design, Stochastic search techniques, Structural optimization

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84894116379&origin=inward
https://hdl.handle.net/11511/72337

Conference Name

2nd International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering, CSC 2011 (6 - 9 Eylül 2011)

Collections

Department of Civil Engineering, Conference / Seminar

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Citation Formats

O. Hasançebi and M. p. Saka, “A reformulation of the ant colony optimization algorithm for large scale structural optimization,” Chania, Crete, Greece, 2011, vol. 97, Accessed: 00, 2021. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84894116379&origin=inward.