A new approach to solve permutation scheduling problems with Ant Colony Optimization

A new approach for solving permutation scheduling problems with Ant Colony Optimization is proposed in this paper. The approach assumes that no precedence constraints between the jobs have to be fulfilled. It is tested with an ant algorithm for the Single Machine Total Weighted Deviation Problem. The new approach uses ants that allocate the places in the schedule not sequentially, as the standard approach, but in random order. This leads to a better utilization of the pheromone information. It is shown that adequate combinations between the standard approach which can profit from list scheduling heuristics and the new approach perform particularly well.