Hybrid Algorithm of Harmony Search, Particle Swarm and Ant Colony for Structural Design Optimization

Abstract

This chapter considers the implementation of the heuristic particle swarm ant colony optimization (HPSACO) methodology to find an optimum design of different types of structures. HPSACO is an efficient hybridized approach based on the harmony search scheme, particle swarm optimizer, and ant colony optimization. HPSACO utilizes a particle swarm optimization with a passive congregation algorithm as a global search, and the idea of ant colony approach worked as a local search. The harmony search-based mechanism is used to handle the variable constraints. In the discrete HPSACO, agents are allowed to select discrete values from the permissible list of cross sections. The efficiency of the HPSACO algorithm is investigated to find an optimum design of truss structures with continuous or discrete search domains and for frame structures with a discrete search domain. The results indicate that the HPSACO is a quite effective algorithm to find the optimum solution of structural optimization problems with continuous or discrete variables.