An improved ant colony optimization for the design of planar steel frames

Abstract

This paper presents an improved ant colony optimization (IACO) for the design of planar steel frames. The algorithm consists of two phases: the global search phase and the local search phase. In the global search phase, IACO employs a sub-optimization mechanism (SOM) based on the principles of finite element methods to reduce the search space, the size of the trail matrix, the number of analyses and consequently the optimization time. In the local search phase, a final optimum design is obtained considering W-shaped sections from the available steel sections specified by the American Institute of Steel Construction (AISC) in the neighborhood of the result gained in the previous phase. The proposed method is tested on several frames from the literature. In order to verify the suitability of the present method, the results of optimum design for several planar steel frames are obtained by the present study and compared to those of the standard ant colony optimization, the genetic algorithm and the harmony search algorithm. The results indicate that the computational time required for the improved ant colony optimization is considerably reduced.