Using chaos-parallel evolutionary programming to solve the flow-shop scheduling problem

In the paper, the chaos-parallel evolutionary programming algorithm is presented to solve the flow-shop scheduling problem. First, the individuals of each sub-population in the parallel evolutionary programming are found in the search space by use of the ergodicity properties of chaos states, then each sub-population evolves independently and the best individuals are exchanged between them periodically. Simulation results demonstrate that the new algorithm is efficient for optimizing large scale manufacturing process and the better results can be achieved on both the calculating time and optimizing rate.