Flight Retiming Revenue Quantification via Iterative Module Forecasting
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Solution Overview
Problem
Current methods for quantifying the revenue and profit impact of retiming airplane flights fail to consider non-linear ramifications and constraints, such as changes in passenger demand, airport slot availability, and operational constraints, leading to suboptimal scheduling that does not maximize revenue.
Innovation Solution
A module-based system that iteratively computes the difference in total demand revenue before and after retiming flights, generating new schedules that take into account the impact on existing and new itineraries, quality of service, and operational feasibility to maximize profit, using a forecasting module, flight grouping module, and scheduling module.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If flight retiming is performed to create new connection opportunities, then additional revenue may be generated, but the complexity of quantifying the impact increases due to non-linear ramifications
Solution Approach 1:
The system segments the complex quantification problem into distinct modules: a forecast module that handles demand prediction, a flight grouping module that manages itinerary combinations, and a scheduling module that coordinates retiming decisions. Each module processes specific aspects of the non-linear ramifications independently, making the overall complex system manageable and computationally tractable
Solution Approach 2:
The patent introduces intermediary computational structures including an origin-destination itinerary database that stores pre-computed connection information, and a quality of service metric that mediates between flight retiming decisions and passenger demand responses. These intermediaries buffer the non-linear relationships, allowing the system to quantify impact without directly solving the full non-linear optimization problem
2Measurement precision
If comprehensive quantification of retiming impact is attempted, then more accurate revenue assessment is achieved, but computation efficiency decreases
Solution Approach 1:
The system performs preliminary actions by pre-computing and storing origin-destination itineraries and their connection relationships in a database before retiming decisions are made. This pre-processing allows the forecast module to quickly assess the impact of potential retiming decisions without performing full recomputations, achieving accurate revenue assessment while maintaining computational efficiency
Solution Approach 2:
The patent applies partial action by focusing computational efforts only on the subset of itineraries and connections that are actually affected by each retiming decision. Rather than re-evaluating the entire flight schedule network, the system identifies and processes only the relevant origin-destination pairs and connecting flights, significantly reducing computation time while maintaining accuracy for the impacted revenue streams
3Productivity
If flight times are changed to optimize revenue, then new connection opportunities arise, but existing connections may be broken
Solution Approach 1:
The system implements feedback mechanisms where the forecast module continuously monitors how retiming decisions affect both new connection opportunities and existing itinerary服务质量. The quality of service metric provides feedback on passenger impact, and this information feeds back into the scheduling module's decision-making process, allowing the system to adjust retiming decisions to balance revenue optimization with connection reliability maintenance
Solution Approach 2:
The patent employs parameter changes by adjusting flight timing parameters within constrained ranges rather than making arbitrary changes. The system evaluates multiple candidate retiming scenarios with different time parameter adjustments, selecting changes that maximize new connection revenue while keeping timing shifts small enough to preserve existing viable connections. This controlled parameter adjustment approach balances opportunity creation with reliability maintenance
4Ease of operation
If manual scheduling is used to maintain simplicity, then operational constraints are easier to manage, but revenue optimization opportunities are missed
Solution Approach 1:
The system applies self-service by implementing automated forecasting and evaluation modules that independently assess revenue impact, compute quality of service metrics, and generate retiming recommendations without requiring manual analysis. The computational system serves itself by automatically processing schedule data, evaluating connections, and identifying optimization opportunities, freeing operators from complex manual scheduling tasks while capturing revenue opportunities that would be missed in manual processes
Data Source
AI summary
A method, system and computer program product for efficiently quantifying the economic impact of retiming flights without the necessity of implementing the traditional airline forecasting system from scratch. A forecast module computes the difference in impact prior to and after the retiming of a flight. A flight grouping module, using the computed difference in impact, generates a new schedule, which is used by the forecast module to generate new changes in impact, until the schedule converges. A flyable module generates a list of retimed flights based on the converged schedule for resolving operational infeasibilities of the latter. The forecast module generates a profit for each of the retimed flights, which is used by a scheduling module to improve the schedule, which is used by the forecast module to revise the economic impacts for the list of all retimed flights. This process continues until no further economic improvement can be made.