Fleet Optimization via Disruption Cost Pricing
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Solution Overview
Problem
Private aircraft fleets face inefficiencies in flight assignment, leading to economic and ecological waste, as well as operational instability, due to the lack of consideration for disruption costs and flexible scheduling, which are not adequately addressed by traditional commercial airline-focused methods.
Innovation Solution
A computerized system, including a floating fleet server, that uses fare estimation and schedule optimization servers to factor in disruption costs and customer preferences, optimizing fleet assignments across multiple operators to minimize total travel time and maximize resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional commercial airline-focused flight assignment methods are used, then operational simplicity is maintained, but resource allocation efficiency deteriorates due to empty relocation flights and lack of disruption cost consideration
Solution Approach 1:
The patent segments the fleet management system into multiple independent operators, each managing their own fleet while contributing to a shared optimization pool. This allows complex multi-operator optimization without requiring a single centralized system to manage all aircraft, thereby improving resource allocation while controlling system complexity through modular architecture
Solution Approach 2:
The patent creates a universal optimization platform that serves multiple private aircraft operators simultaneously. The system handles diverse fleet configurations, different operational requirements, and various disruption scenarios through a single multi-functional framework, improving overall resource allocation efficiency across the entire ecosystem
2Adaptability or versatility
If empty relocation flights are used to reposition aircraft between drop off and pick up locations, then operational flexibility is maintained, but economic and ecological waste increases
Solution Approach 1:
The patent merges the relocation needs of multiple operators into a shared pool, allowing aircraft from one operator to fulfill another operator's relocation requirements. This combines previously separate relocation operations into coordinated flights, reducing empty repositioning while maintaining the flexibility needed to meet customer demands across the network
Solution Approach 2:
The system performs preliminary optimization calculations that proactively identify and eliminate unnecessary empty relocation flights before they occur. By pre-planning fleet assignments across multiple operators and considering future demand patterns, the system avoids scheduling wasteful empty flights while preserving operational flexibility for genuine customer needs
3Reliability
If disruption costs are not factored into fare estimation, then pricing simplicity is maintained, but operational stability deteriorates due to inadequate scheduling optimization
Solution Approach 1:
The patent implements feedback mechanisms where disruption costs calculated from schedule optimization are fed back into the fare estimation process. This creates a closed-loop system where pricing reflects actual operational impacts, and the resulting revenue feedback further refines scheduling decisions, improving operational stability through data-driven iterative optimization
Solution Approach 2:
The system performs preliminary disruption cost calculations during the fare estimation phase, before flights are assigned and potential disruptions occur. This advance calculation allows operators to price flights with their true operational costs built in, enabling better financial planning and more stable operations without requiring complex real-time adjustments during flight execution
Data Source
AI summary
A request is received to book a flight on a private aircraft. A disruption cost associated with adding the flight to a previously optimized schedule of previously booked flights is determined. A price to be quoted to book the requested flight is computed based at least in part on the disruption cost.