Dynamic scheduling of carrier aircraft based on improved ant colony algorithm under disruption and strong constraint

Abstract

Aircraft scheduling is a typical dynamic scheduling problem when carrying out certain missions. Due to unfixed mission, disruption and limited time, space and resources, aircraft scheduling generally has strong constraint and many uncertainties. In this paper, we propose an improved direct graph to describe the complex scheduling process. We add the temporary point to deal with the strong constraint, and all disturbance are processed as the occupation of nodes and path. The objectives for planning scheduling strategies to shift the aircrafts among nodes on direct graph containing the occupancy with better scheduling efficiency, cost and reliability. Then, we given an optimal algorithm based on improved ant colony optimization (ACO) to find optimal scheduling strategy. Finally, with a simple case, the effectiveness of the model and algorithm is verified. And the given algorithm can basically solve path planning and resource allocation problems for the scheduling system which is often influenced by uncertain disturbances. And in the scheduling process, we reduce the waste of resources, get rid of conflicts in using, and increase the reliability as much as possible.