An Improved Ant Colony Model for Cost Optimization of Composite Beams. Issue 1 (2nd January 2017)

• Record Type: Journal Article
• Authors: Korouzhdeh, Tahereh; Eskandari-Naddaf, Hamid; Gharouni-Nik, Morteza
• Is Part Of: Applied artificial intelligence. Volume 31:Issue 1(2017)
• Page Start: 44
• Page End: 63
• Publication Date: 2017-01-02
• Subjects: Artificial intelligence -- Periodicals; 006.3
• DOI: 10.1080/08839514.2017.1296681
• Languages: English
• ISSNs: 0883-9514

Abstract

ABSTRACT: This paper focused on the application and evaluation of an improved ant colony search method for the cost optimization of composite beams. The design was based on the American Institute of Steel Construction load and resistance factor design specifications and plastic design concepts. The objective function for composite beam was the cost function. This function included the cost of concrete, steel beam, and shear connectors. In order to validate the proposed model in optimizing composite beam design, two design examples taken from the literature were studied, and the results were compared to the original ant colony optimization and other meta-heuristic algorithms. The results showed that the improved ant colony method was able to find better solutions and had higher convergence speed than other meta-heuristic algorithms. Moreover, a parametric study was conducted to investigate the effects of beam spans and loadings on the cost optimization of composite beams.