A dual population multi-operator genetic algorithm for flight deck operations scheduling problem

It is of great significance to carry out effective scheduling for the carrier-based aircraft flight deck operations. In this paper, the precedence constraints and resource constraints in flight deck operations are analyzed, then the model of the multi-aircraft integrated scheduling problem with transfer times (MAISPTT) is established. A dual population multi-operator genetic algorithm (DPMOGA) is proposed for solving the problem. In the algorithm, the dual population structure and random-key encoding modified by starting/ending time of operations are adopted, and multiple genetic operators are self-adaptively used to obtain better encodings. In order to conduct the mapping from encodings to feasible schedules, serial and parallel scheduling generation scheme-based decoding operators, each of which adopts different justified mechanisms in two separated populations, are introduced. The superiority of the DPMOGA is verified by simulation experiments.

Automated summary

This paper analyzes precedence and resource constraints in carrier-based aircraft flight deck operations, establishes the MAISPTT model, and proposes a DPMOGA algorithm to solve the integrated scheduling problem. The superiority of DPMOGA is verified through simulation experiments.