An Efficient Continuous-Time MILP for Integrated Aircraft Hangar Scheduling and Layout

• URL: http://arxiv.org/abs/2508.02640v1
• Date: Mon, 04 Aug 2025 17:25:36 GMT
• Title: An Efficient Continuous-Time MILP for Integrated Aircraft Hangar Scheduling and Layout
• Authors: Shayan Farhang Pazhooh, Hossein Shams Shemirani,
• Abstract summary: This paper introduces a novel continuous-time mixed-integer linear programming (MILP) model to solve this integrated-temporal problem.<n>The model solves instances with up to 25 aircraft to proven optimality, often in mere seconds, and for large-scale cases of up to 40 aircraft, delivers high-quality solutions within known optimality gaps.<n>In all tested scenarios, the framework's substantial economic benefits and provides valuable managerial insights into the trade-off between solution time and optimality.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Efficient management of aircraft maintenance hangars is a critical operational challenge, involving complex, interdependent decisions regarding aircraft scheduling and spatial allocation. This paper introduces a novel continuous-time mixed-integer linear programming (MILP) model to solve this integrated spatio-temporal problem. By treating time as a continuous variable, our formulation overcomes the scalability limitations of traditional discrete-time approaches. The performance of the exact model is benchmarked against a constructive heuristic, and its practical applicability is demonstrated through a custom-built visualization dashboard. Computational results are compelling: the model solves instances with up to 25 aircraft to proven optimality, often in mere seconds, and for large-scale cases of up to 40 aircraft, delivers high-quality solutions within known optimality gaps. In all tested scenarios, the resulting solutions consistently and significantly outperform the heuristic, which highlights the framework's substantial economic benefits and provides valuable managerial insights into the trade-off between solution time and optimality.

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