Airline Schedule Robustness Optimization via Simulation Feedback
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Solution Overview
Problem
Airline traffic network planning is typically optimized months in advance, while the evaluation of its robustness occurs near the time of execution, leading to a disconnect between these two processes, making it difficult for airlines to quantify and evaluate the robustness of their schedules effectively.
Innovation Solution
A system integrating an optimization module and a robustness analysis module in a closed-loop feedback system to optimize airline schedules and evaluate their robustness, using algorithms and simulation-based methods to consider various objectives and disturbances, thereby providing a more robust and efficient network planning process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If airline schedule optimization is performed months in advance, then planning time is sufficient for comprehensive optimization, but the robustness evaluation cannot be performed until after execution, creating a disconnect between optimization and evaluation
Solution Approach 1:
The patent applies preliminary action by performing robustness evaluation through simulation before the actual schedule execution. The system uses historical data and simulated disturbances to assess robustness in advance, allowing airlines to identify and correct potential issues before they impact real operations. This resolves the timing disconnect by enabling both optimization and robustness evaluation to occur in the planning phase rather than separating them by months.
Solution Approach 2:
The patent implements feedback by creating a closed-loop system where robustness evaluation results feed back into the optimization process. The system uses simulation outcomes and robustness metrics to iteratively refine schedule plans, allowing continuous improvement between optimization and evaluation. This feedback mechanism ensures that robustness considerations are integrated into the optimization rather than being a separate post-execution assessment.
2Ease of operation
If traditional separate processes are used for optimization and robustness evaluation, then each process can be performed independently, but the airline cannot effectively quantify and evaluate the robustness of flight schedules
Solution Approach 1:
The patent merges previously separate optimization and robustness evaluation processes into an integrated system. The optimization module and robustness analysis module work together in a unified platform that combines schedule optimization with real-time robustness assessment. This integration allows airlines to simultaneously optimize schedules while quantifying robustness metrics, eliminating the need for separate independent processes and enabling precise robustness measurement throughout the planning and execution phases.
3Reliability
If robustness evaluation is performed near execution time, then the evaluation reflects actual operating conditions, but the optimization cannot incorporate robustness considerations from the planning phase
Solution Approach 1:
The patent uses simulation as an intermediary that bridges the gap between planning-phase optimization and execution-phase robustness assessment. The simulation environment replicates actual operating conditions and disturbance scenarios, allowing robustness evaluation in advance while maintaining realism. This intermediary enables optimization algorithms to incorporate robustness considerations by using simulation results to inform optimization decisions, combining the benefits of early planning with accurate robustness assessment.
Data Source
AI summary
A method, medium, and system to receive a baseline airline schedule including details associated with at least one flight; optimize the baseline airline schedule in accordance with at least one specified optimization objective to generate an optimized airline schedule; evaluate a robustness of the optimized airline schedule based on an execution of a simulation based process to generate a set of quantitative metrics; and generate a record of the set of quantitative metrics.