A time-varying competitive swarm optimizer for integrated flight recovery with multi-objective and priority considerations

Integrating aircraft and crew recovery is a growing topic in providing an efficient recovery system after a disruption. Most existing models only conduct from airline perspective and treat all disturbed flights homogeneously. However, in a realistic operation, the decision objectives are multiple with the interplay of stakeholders. Moreover, flights with first-aid items hold special priority. Thus, this paper presents a new Integrated Aircraft and Crew Recovery with Multi-objective and Priority, namely IACR_MP. To solve IACR_MP efficiently, an ad-hoc particle swarm optimization-based optimizer is designed. Time-varying tri-competition with different evolutionary mechanisms is developed to achieve a balance between exploitation and exploration capacities. Three repair schemes are built to prevent low feasibility caused by high constraints, and a self-exploration strategy is used to detect the potential zones of contemporary non-dominated solutions. Finally, six instances with different scales are used for algorithm performance analyses. Results illustrate that our algorithm has good solution quality and significantly outperforms its competitors in solving the IACR_MP. Moreover, our framework can provide a series of specific recovery schemes, providing decision support with more choices to airline managers.