Aircraft Fleet Assignment Using Optimization for Airport Slot Matching
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Solution Overview
Problem
The process of aligning flight schedules with allocated slots at airports is time-consuming and difficult due to conflicts between schedule intentions and available slots, with limited ability to make slight changes without affecting other airlines.
Innovation Solution
A computer system and method that creates a model to align flights with allocated slots using mixed integer linear programming or machine learning models, optimizing flight schedules to achieve extrema based on objectives such as revenue, operating costs, and turn-time buffers, allowing for adjustments and slot swaps to improve alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual schedule revision is used to align flights with slots, then schedule-slot alignment is achieved, but the process is time-consuming and labor-intensive
Solution Approach 1:
The patent replaces manual mechanical schedule revision processes with an automated computer system that uses optimization algorithms. The system automatically adjusts flight schedules to align with allocated slots by processing input data, generating multiple schedule options, and selecting optimal alignments without human intervention, thereby reducing time consumption while maintaining alignment precision.
Solution Approach 2:
The system changes schedule parameters (flight times, dates, routes) automatically based on allocated slot parameters. By using optimization models that consider multiple constraints and objectives, the system dynamically adjusts schedule parameters to achieve optimal alignment with slots, transforming a manual parameter adjustment process into an automated computational process.
2Productivity
If schedule changes are made to align with slots, then slot utilization improves, but other airlines' schedules may be affected
Solution Approach 1:
The patent segments the schedule alignment problem into individual airline optimizations. The system processes each airline's schedule independently, using their specific constraints and objectives, while considering slot availability across the airport system. This segmentation allows optimized alignment for each airline without automatically propagating changes that would harm other carriers.
Solution Approach 2:
The system incorporates feedback mechanisms that consider the impact of schedule changes on the overall airport ecosystem. By evaluating multiple schedule options and their consequences, the system can select alignments that optimize slot utilization for each airline while maintaining compatibility with other airlines' operations, effectively managing the harmful effects of schedule changes.
3Manufacturing precision
If slot changes are requested to align with schedule intentions, then schedule-slot alignment improves, but the negotiation process is complex and time-consuming
Solution Approach 1:
The system enables self-service schedule optimization by automatically generating aligned schedules without requiring extensive negotiation with slot coordinators. The computer system independently processes slot data, generates multiple alignment options, and selects optimal schedules based on predefined criteria, eliminating the need for complex manual negotiation processes while achieving precise alignment.
Solution Approach 2:
The system performs preliminary actions by pre-processing slot data and generating multiple potential schedule alignments before final selection. By preparing and evaluating multiple options in advance using optimization algorithms, the system reduces the complexity of final decision-making and negotiation, as the most viable options are already identified and validated.
4Productivity
If flights are aligned to slots using optimization models, then alignment efficiency improves, but computational complexity increases
Solution Approach 1:
The patent segments the computational optimization into manageable components, processing each airline's schedule separately with dedicated constraints and objectives. This segmentation reduces the complexity of any single optimization problem while maintaining overall alignment efficiency across the entire fleet, allowing the system to handle large-scale problems through divided computational tasks.
Data Source
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AI summary
A method, apparatus, system, and computer program product for managing slots. The slots allocated to an airline are identified by computer system. A model that describes a relationship of flights in an input flight schedule and the slots that have been allocated subject to constraints is created by the computer system. An output flight schedule is created by the computer system using the model to obtain an extrema using a set of objectives. The flights are aligned to the slots in the output flight schedule.