## 1 Introduction
[PERSON] [18] designed a human-computer cooperation decision planning system (aircraft carrier deck operation planner (ACDOP) system). [PERSON] [19] proposed a multi-agent based fleet maintenance personnel configuration method to solve the mission-oriented aircraft fleet maintenance personnel configuration problem. [PERSON] [20] viewed the flight deck scheduling problem as an extension of the flexible job shop scheduling problem (FJSP), and designed an improved differential evolution algorithm (IDE) to improve the computational efficiency. Our research team has also published some relevant papers for the carrier aircraft scheduling problem including the constraints in the scheduling [21], the multi-objective integrated supporting scheduling model, and the intelligence algorithm to solve this problem [22; 23]. Compared with other land-based aircraft [24; 25], the flight deck in an aircraft carrier presents a complex and uncertain environment in which time-critical scheduling and planning must be done to fulfill mission requirements and ensure the safety of operational crews and equipment [26]. However, most previous research has been aimed at developing better solution methods or scheduling strategies based on a static scheduling environment, and most research is oversimplified. The related literatures regarding managing and guiding the carrier aircraft operations and scheduling are very limited. The strong constraints in the operations usually result in a lot of dynamic scheduling disruptions. The research about the dynamic scheduling method of carrier aircraft support and operation is more important and complicated, but there has not been enough. The carrier aircraft dynamic scheduling, which is a special RCPSP and considered as multi-resource constrained multi-project scheduling problem (MRCMPSP) under uncertain environments, may face a lot of significant disruptions due to resource unavailability, duration deviation, machine breakdowns, operator variation, and uncertain tasks. The traditional deterministic scheduling strategy must be revised and resolved in order to increase the resource utilization and respond to the changing flight deck environment. In order to find optimal solutions under uncertainty, some primary types of existing rescheduling strategies have been researched, such as the reactive scheduling strategy [27], the proactive scheduling strategy [28], and robust execution strategies [29]. In flight deck carrier aircraft scheduling research, [PERSON] [30] has researched aircraft carrier flight deck dynamic planning based on a dynamic hierarchical task network (HTN) planning process for a set of activities with resource constraints. However, the twofold network structure is simple, and still has some limitations. [PERSON] [31] integrated the robust schedule design with fleet assignment and aircraft routing problems in a dynamic environment. This made it possible to improve the solution, since a routing decision could eliminate the necessity of inserting idle time or compressing cruise time, but it could not make a real-time decision when unpredictable disruptions occurred and the robust schedule needed to be rescheduled. [PERSON] [32] described how the RCPSP can be used as a basis for real-time decision support in the disruption management of the aircraft turnaround, and argued that the RCPSP dynamic scheduling research for carrier aircraft is significant; however, it is only partial research that did not sufficiently deal with the uncertain random interferences. In other dynamic scheduling research, copious algorithms and methods can be found in the literature such as the branch and bound algorithm [33], the linear programming-based algorithm [34], and other exact algorithms [35], and many heuristic algorithms and metaheuristic algorithms have been also presented in the literature such as the genetic algorithm [36] (GA), hybrid GA [37], and differential evolution (DE) [38].