Airline Crew Trade Optimization Network

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Solution Overview

Problem

Current systems for trading trip assignments among airline crew members based on seniority and equity are inefficient, as they often result in infeasible solutions due to conflicting trade requests and lack transparency in the fulfillment process.

Innovation Solution

A system and method that utilize an optimization network with nodes representing trade requests and directional arcs representing supply-to-demand relationships, ranking nodes by seniority and equity, and using mixed-integer programming to maximize flow and ensure legal trades, while incorporating weighted arcs for nested requests and multi-drop/pick-up scenarios.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If current systems are used for trading trip assignments, then the process is simple to operate, but the solutions are infeasible due to conflicting trade requests and lack transparency

Engineering Contradiction:

Improvefeasibility of trade solutionsVSAvoidcomplexity of optimization network

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system segments the trade request fulfillment process into discrete nodes representing individual requests and directional arcs representing supply-to-demand relationships. This segmentation allows the complex optimization problem to be broken down into manageable components that can be processed systematically through mixed-integer programming, resolving conflicts between multiple trade requests while maintaining feasibility.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The optimization network acts as an intermediary between trade requests and fulfillment outcomes. It introduces directional arcs as intermediary elements that represent supply-to-demand relationships, enabling the system to mediate conflicting requests through mathematical optimization rather than direct conflict resolution, thereby ensuring feasible solutions.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Loss of information

If traditional trade fulfillment methods are used, then the system is easy to operate, but transparency in the fulfillment process is lacking

Engineering Contradiction:

Improvetransparency of fulfillment processVSAvoidcomplexity of optimization network

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The system incorporates feedback mechanisms by ranking nodes according to seniority and equity criteria and using mixed-integer programming to maximize flow through the network. This feedback loop ensures that fulfillment decisions are transparent and can be traced back through the optimization network, allowing stakeholders to understand how conflicting requests are resolved based on established priorities.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system performs preliminary actions by pre-ranking nodes according to seniority and equity before fulfillment. This preliminary structuring of the optimization network ensures that transparency is built into the system architecture itself, with the ranking criteria and supply-to-demand relationships established before the optimization process begins.

Inventive Principle:

Principle #10Preliminary action

3Productivity

If manual monitoring of trade requests is used, then the system is simple, but more pilot monitoring is required and fewer requests are satisfied

Engineering Contradiction:

Improvenumber of requests satisfiedVSAvoidautomation of trade fulfillment

Core Design Contradiction:

ProductivityVSExtent of automation

Solution Approach 1:

The system enables self-service automation through the optimization network, which automatically processes trade requests according to seniority and equity criteria without requiring manual pilot monitoring. The mixed-integer programming formulation maximizes flow through the network, automatically satisfying the maximum number of feasible requests while eliminating the need for manual intervention.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system changes parameters by transforming the trade fulfillment problem into a mixed-integer programming optimization problem with specific objective functions and constraints. This parameter transformation enables automated processing of trade requests, maximizing the number of satisfied requests through mathematical optimization rather than manual evaluation.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS9159041B1System and method of fulfilling trade requests corresponding to airline flight sequences by generating optimization network

Publication Date: 2015.10.13 AMERICAN AIRLINES INC

AI summary

A system and method according to which data associated with a plurality of trade requests is received, and an optimization network is generated, the optimization network including a plurality of nodes corresponding to the trade requests. The nodes are ranked in accordance with at least one business objective, and one or more of the requests are fulfilled in an order based on the ranking of the nodes. To fulfill the one or more requests, a solution is generated, the solution complying with one or more predetermined rules. In an exemplary embodiment, each of the trade requests corresponds to a request to trade a work assignment. In an exemplary embodiment, each trade request is a request by an airline crew member to trade an airline flight sequence, and the at least one business objective is based on airline crew member seniority.