Bi-directional convergence ACO for job-shop scheduling

To properly and efficiently schedule resources and solve the combinatorial optimization problem, an improved algorithm named Bi-directional Convergence Ant Colony Optimization (ACO) algorithm was proposed. Using the graphic definition of Job-shop problem and the elitist strategy, the Bi-directional Convergence ACO algorithm was designed to improve efficiency and usability of original ACO by different evaporated means. Finally, the Bi-directional Convergence ACO algorithm was tested on a benchmark Job-shop scheduling problem. The performance of the Bi-directional Convergence ACO was also compared with that of the original ACO. The simulation result illustrates that the bi-directional convergence ACO algorithm accelerates the convergence without affecting the temporal and spatial complexity much.