A time-triggered dimension reduction algorithm for the task assignment problem

Wang, Han; Margellos, Kostas; Papachristodoulou, Antonis

doi:10.1016/j.ejcon.2022.100692

Cited by 1 publication

(1 citation statement)

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“…As for constraint (5), it stipulates that flights can only undergo de-icing operations in one de-icing position at any given time. Moreover, constraints (7) to (9) outline the relationships among the earliest feasible de-icing pad entry time, the de-icing duration for Type K flights, and the actual departure time of flights, encompassing various time variables. These equations lay the groundwork for calculating the time constraints in the upper-level model, denoted as constraint (6).…”

Section: Upper-level Modeling-aircraft Scheduling Problem With Finite...mentioning

confidence: 99%

Bi-Level Optimization for De-Icing Position Allocation and Unmanned De-Icing Vehicle Fleet Routing Problem

Liu,

Huang,

Han

et al. 2024

Biomimetics

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Aircraft icing due to severe cold and local factors increases the risk of flight delays and safety issues. Therefore, this study focuses on optimizing de-icing allocation and adapting to dynamic flight schedules at medium to large airports. Moreover, it aims to establish a centralized de-icing methodology employing unmanned de-icing vehicles to achieve the dual objectives of minimizing flight delay times and enhancing airport de-icing efficiency. To achieve these goals, a mixed-integer bi-level programming model is formulated, where the upper-level planning guides the allocation of de-icing positions and the lower-level planning addresses the collaborative scheduling of the multiple unmanned de-icing vehicles. In addition, a two-stage algorithm is introduced, encompassing a Mixed Variable Neighborhood Search Genetic Algorithm (MVNS-GA) as well as a Multi-Strategy Enhanced Heuristic Greedy Algorithm (MSEH-GA). Both algorithms are rigorously assessed through horizontal comparisons. This demonstrates the effectiveness and competitiveness of these algorithms. Finally, a model simulation is conducted at a major northwestern hub airport in China, providing empirical evidence of the proposed approach’s efficiency. The results show that research offers a practical solution for optimizing the use of multiple unmanned de-icing vehicles in aircraft de-icing tasks at medium to large airports. Therefore, delays are mitigated, and de-icing operations are improved.

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Section: Upper-level Modeling-aircraft Scheduling Problem With Finite...mentioning

confidence: 99%