Branch-and-Bound Global-Search Algorithm for Aircraft Ground Movement Optimization

Optimal aircraft ground scheduling is a well-known nondeterministic polynomial-time-hard problem; hence, many heuristics are used to generate schedules within realistic runtimes. These heuristics are designed to run fast, but they often do not promise any guarantee about the solution quality. Inspired by two existing algorithms for scheduling of railway operations, this paper introduces a branch-and-bound-based aircraft routing and scheduling approach with guaranteed global optimality as a real-time decision support tool for air traffic controllers. The performance of the algorithm is benchmarked against two previous approaches: a combinatorial approach using mixed-integer linear programming, and a heuristic approach based on bacterial foraging. The configuration agnostic design of the algorithm makes it suitable for applications: even to unconventional airport layouts. The globally optimal nature of the current solution exhibits a distinct improvement over the respective solutions while maintaining minimal runtimes. The algorithm is tested for flight operations at the cross-runway configuration of the Mumbai International Airport and delivers better and quicker solutions compared to previous studies.