Flight Schedule Robustness Evaluation via Simulation
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Solution Overview
Problem
Airlines lack effective and efficient means to evaluate the robustness of their flight schedules, which are typically planned months in advance, and are only assessed for robustness after execution, making it difficult to quantify and validate schedule robustness in real-time.
Innovation Solution
A method and system using a model-based simulation and analysis module to evaluate and validate the robustness of flight schedules, including automatic generation of test schedules to cover various operation possibilities, providing quantitative metrics for robustness assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If flight schedules are planned many months in advance, then schedule stability is improved, but the ability to evaluate and validate robustness before execution deteriorates
Solution Approach 1:
The system performs preliminary robustness evaluation through simulation-based testing before the flight schedule is executed. Test schedules are automatically generated and evaluated using historical data and quantitative metrics to assess robustness in advance, allowing airlines to validate and improve schedules before real-world operation without compromising the months-advance planning timeline
2Measurement precision
If robustness evaluation is performed after schedule execution, then measurement accuracy is improved, but loss of time and opportunity for improvement increases
Solution Approach 1:
The system creates virtual copies of flight schedules through simulation models that replicate real-world operations. These test schedules are subjected to various disruption scenarios in a virtual environment, allowing accurate robustness measurement without waiting for actual execution. The simulation-based approach provides timely evaluation results that can be used to improve schedules before real operation
3Measurement precision
If quantitative metrics are introduced for robustness assessment, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system introduces simulation-based test schedules as an intermediary between the actual flight schedule and the robustness evaluation process. These virtual test cases mediate the assessment by subjecting the schedule to controlled disruption scenarios, enabling quantitative metric calculation without requiring complex direct measurement instruments during real operations
Data Source
AI summary
A method, medium, and system to receive a planned flight schedule and an actual flight schedule; determine root cause disturbances for the actual flight schedule based on the planned flight schedule and the actual flight schedule; evaluate a robustness of the planned flight schedule based on an execution of a simulation-based model to generate a set of quantitative metrics for the planned flight schedule; generate a record of the root cause disturbances and a record of the set of quantitative metrics for the planned flight plan; evaluate a robustness of a test flight schedule based on an execution of the simulation-based model and the determined root cause disturbances applied to the simulation-based model to generate a set of quantitative metrics for the test flight schedule; and generate a record of the set of quantitative metrics for the test flight plan.