Design of Space Trusses Using Ant Colony Optimization

Abstract

A design procedure utilizing an ant colony optimization (ACO) technique is developed for discrete optimization of space trusses. The objective function considered is the total weight (or cost) of the structure subjected to material and performance constraints in the form of stress and deflection limits. The design of space trusses using discrete variables is transformed into a modified traveling salesman problem (TSP) where the network of the TSP reflects the structural topology and the length of the TSP tour is the weight of the structure. The resulting truss, mapped into a TSP, is minimized using an ACO algorithm. The ACO design procedure uses discrete design variables, an open format for prescribing constraints, a penalty function to enforce design constraints, and allows for multiple loading cases. A comparison is presented between the ACO truss design procedure and designs developed using a genetic algorithm and classical continuous optimization methods.