ENGINEERING OPTIMIZATION WITH HYBRID PARTICLE SWARM AND ANT COLONY OPTIMIZATION

This article presents a heuristic particle swarm ant colony optimization algorithm to solve engineering optimization problems. Although PSO has simple principle and ease to be implemented and can eventually locate the desired solution, however, its practical use in solving engineering optimization problems is severely limited by the high computational cost of the slow convergence rate. Here, ant colony and harmony search principles are employed to speed up local search and improve precision of the solutions. A modified feasible-based mechanism is described which handles the problem-specific constraints. Benchmark optimization problems are used to illustrate the reliability of the proposed algorithm.