Method and system for robust network planning optimization of airline flight operations

Patent metadata

Field	Value
Publication number	US-2016203722-A1
Application number	US-201514593578-A
Country	US
Kind code	A1
Filing date	Jan 9, 2015
Priority date	Jan 9, 2015
Publication date	Jul 14, 2016
Grant date	—

Abstract

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.

First claim

What is claimed is:

1 . A system comprising:
a communication device operative to receive a baseline airline schedule including details associated with at least one flight; an optimization module to receive the baseline airline schedule from the communication device and optimize the baseline airline schedule; a robustness analysis module to receive the optimized airline schedule and evaluate the robustness thereof; a memory to store program instructions; and at least one processor coupled to the memory and in communication with the optimization module and the robustness analysis module, the at least one processor being operative to execute program instructions to:
optimize, by the optimization module, the baseline airline schedule in accordance with at least one specified optimization objective to generate an optimized airline schedule;
evaluate, by the robustness analysis module, 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.

2 . The system of claim 1 , wherein the robustness analysis module further:
determines whether the evaluated robustness of the optimized airline schedule satisfies a predetermined threshold robustness value; in an instance the evaluated robustness of the optimized airline schedule satisfies the predetermined threshold robustness value, proceeds to generate the record the set of quantitative metrics; and in an instance the evaluated robustness of the optimized airline schedule does not satisfy the predetermined threshold robustness value, uses the generated set of quantitative metrics to further optimize and evaluate the robustness of the optimized airline schedule based on updated parameter settings.

3 . The system of claim 1 , wherein the details associated with the at least one flight include at least one of a flight number, a flight departure time, a flight arrival time, a flight departure airport, a flight arrival airport, an aircraft type for the at least one flight, flight crew details for the at least one flight, other specific information related to the flight including but not limited to desired city pairs, desired flight times, block times, aircraft assets, airports, airport gate assignments, ground crews, flight crews, and combinations thereof.

4 . The system of claim 1 , wherein the optimization module executes the optimization using at least one algorithm from a suite of algorithms, the suite of algorithms including at least one of a connection-based algorithm, a string-based algorithm, an artificial intelligence algorithm, and other heuristics-based algorithms and a particular optimization algorithm executed depends on a user specification, a complexity of the optimization, and a combination thereof.

5 . The system of claim 1 , wherein the at least one specified optimization objective is based on at least one of a revenue plan, traffic intensity, traffic pattern, aircraft turn time, airport flow rate, and recovery opportunity.

6 . The system of claim 1 , wherein the robustness analysis module that executes the simulation based process to generate the set of quantitative metrics considers, at least in part, at least one of identified root causes of airline operation disturbances, user-defined disturbances, and hypothetical disturbances.

7 . A method implemented by a computing system in response to execution of program instructions by a processor of the computing system, the method comprising:
receiving a baseline airline schedule including details associated with at least one flight; optimizing the baseline airline schedule in accordance with at least one specified optimization objective to generate an optimized airline schedule; evaluating a robustness of the optimized airline schedule based on an execution of a simulation based process to generate a set of quantitative metrics; and generating a record of the set of quantitative metrics.

8 . The method of claim 7 , further comprising:
determining whether the evaluated robustness of the optimized airline schedule satisfies a predetermined threshold robustness value; in an instance the evaluated robustness of the optimized airline schedule satisfies the predetermined threshold robustness value, proceeding to generate the record the set of quantitative metrics; and in an instance the evaluated robustness of the optimized airline schedule does not satisfy the predetermined threshold robustness value, using the generated set of quantitative metrics to further optimize and evaluate the robustness of the optimized airline schedule based on updated parameter settings.

9 . The method of claim 7 , wherein the details associated with the at least one flight include at least one of a flight number, a flight departure time, a flight arrival time, a flight departure airport, a flight arrival airport, an aircraft type for the at least one flight, flight crew details for the at least one flight, other specific information related to the flight including but not limited to desired city pairs, desired flight times, block times, aircraft assets, airports, airport gate assignments, ground crews, flight crews, and combinations thereof.

10 . The method of claim 7 , wherein the optimization is performed using at least one algorithm from a suite of algorithms, the suite of algorithms including at least one of a connection-based algorithm, a string-based algorithm, an artificial intelligence algorithm, and other heuristics-based algorithms and a particular optimization algorithm used depends on a user specification, a complexity of the optimization, and a combination thereof.

11 . The method of claim 7 , wherein the at least one specified optimization objective is based on at least one of a revenue plan, traffic intensity, traffic pattern, aircraft turn time, airport flow rate, and recovery opportunity.

12 . The method of claim 11 , wherein the recovery opportunity is characterized by a duration of aircraft turn, a time of day of aircraft turn, and a location of aircraft turn.

13 . The method of claim 7 , wherein the simulation based process to generate the set of quantitative metrics considers, at least in part, at least one of identified root causes of airline operation disturbances, user-defined disturbances, and hypothetical disturbances identified root causes of airline operation disturbances.

14 . A non-transitory, computer-readable medium storing instructions that, when executed by a computer processor, cause the computer processor to perform a method associated with a robust network planning optimization, the medium comprising program instructions executable by the computer processor 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.

15 . The medium of claim 14 , further comprising program instructions executable by the computer processor to:
determine whether the evaluated robustness of the optimized airline schedule satisfies a predetermined threshold robustness value; in an instance the evaluated robustness of the optimized airline schedule satisfies the predetermined threshold robustness value, proceed to generate the record the set of quantitative met

Assignees

• Gen Electric

Inventors

• Liao Hongwei
• Aragones James Kenneth
• Bhaskar Nitika
• Dunsdon Jonathan Mark

Classifications

• G06Q10/04 Primary

  Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" (market predictions or forecasting for commercial activities G06Q30/0202) · CPC title

• G08G5/56

  for two or more aircraft · CPC title

• G08G5/34

  for flight plan modification · CPC title

• G08G5/20

  Arrangements for acquiring, generating, sharing or displaying traffic information (arrangements for monitoring traffic G08G5/72) · CPC title

• G08G5/00 Primary

  Traffic control systems for aircraft · CPC title