Granted Patent B1

US 12,530,978 · App. 19/005,840 · Granted Jan 20, 2026

Inventors: Suat Bog (Los Angeles, CA); Yu-Heng Chang (Austin, TX); Izzy Doctor (Los Angeles, CA)

Assignee: Wheels Up Partners Holdings LLC

G08G5/32G06Q10/047G06Q50/40

Abstract

Claims (123)

1 . A computer implemented method performed by one or more processors for constructing and modifying a schedule for an on-demand private aviation operator, the computer implemented method comprising:

at least one of obtaining or accessing demand information including a respective flight demand for each customer of a plurality of customers that have requested to fly from a respective departure location to a respective destination location departing at a respective time and day of one or more specific days in the future;

at least one of obtaining or accessing supply information including a respective availability for each of a plurality of aircraft and for each of a plurality of crew members on the one or more specific days in the future;

using a construction algorithm to construct a schedule for the one or more specific days in the future that satisfies the flight demands of the customers and optimizes the schedule to achieve one or more objectives of the construction algorithm while complying with constraints related to the aircraft, the crew members, and the customers;

wherein the schedule constructed using the construction algorithm assigns respective aircraft to respective aircraft routes each of which includes one or more flight legs, and assigns respective crew members to the respective aircraft routes or one or more of the flight legs thereof; and

wherein each said flight leg of each of said aircraft route may be used to satisfy at least a portion of a said flight demand of a said customer; and

on one of the one or more specific days or within a specified temporal period prior thereto, receiving an indication of a change to at least one of the supply information or the demand information that warrants a modification to the schedule, and in response thereto, using an improvement algorithm that differs from the construction algorithm to modify a portion of the schedule to achieve one or more objectives of the improvement algorithm while complying with the constraints related to the aircraft, the crew members, and the customers;

wherein the using the improvement algorithm to modify the portion of the schedule to achieve the one or more objectives of the improvement algorithm while complying with the constraints related to the aircraft, the crew members, and the customers, includes:

constructing a graph data model by

generating an initial feasible solution (IFS) that can be used to satisfy a said flight demand for a said customer that is in recovery because of the change to at least one of the supply information or the demand information that warrants the modification to the schedule; and

creating and populating node layers and nodes of a graph data model corresponding to the IFS and constructing arcs between different ones of the nodes included in different ones of the node layers, such that: each of the nodes in the graph data model corresponds to a respective flight demand, each of the node layers in the graph data model corresponds to a respective aircraft route that can be used to satisfy one or more of the flight demands, one of the nodes in the graph data model corresponds to the said flight demand that is in recovery, one of the node layers in the graph data model corresponds to an aircraft route that can be used to satisfy the said flight demand that is in recovery, and the arcs in the graph data model define links between pairs of the nodes included in different ones of the node layers;

performing a neighborhood search on the graph data model, which includes iteratively identifying improvements in the graph data model by iteratively identifying one or more negative cost cycles (NCCs) until a specified criterion is satisfied; and

modifying the portion of the schedule, based on results of the neighborhood search performed on the graph data model, to achieve the one or more objectives of the improvement algorithm while complying with the constraints related to the aircraft, the crew members, and the customers.

2 . The method of claim 1 , wherein the using the construction algorithm to construct the schedule for the one or more specific days in the future, comprises:

performing route enumeration to produce a list of feasible aircraft routes that can be used to satisfy the flight demands of the plurality of customers on the one or more specific days using those of the plurality of aircraft available on the one or more specific days;

performing route selection to select, from the list of feasible aircraft routes produced as a result of performing the route enumeration, a shortened list of the feasible aircraft routes that can be used to satisfy the flight demands of the plurality of customers on the one or more specific days using those of the plurality of crew members available on the one or more the specific days; and

performing route optimization to select, from the shortened list of the feasible aircraft routes, a respective single aircraft route for each of the aircraft included in the schedule, respective crew members for each of the respective flight legs, and a respective single flight leg for each of the flight demands of the plurality of customers,

wherein the route optimization optimizes the schedule to achieve one or more objectives of the construction algorithm while complying with the constraints related to the aircraft, the crew members, and the customers.

3 . The method of claim 2 , wherein one or more objectives of the construction algorithm include one or more of the following:

maximize revenues;

minimize costs;

maximize profits;

minimize flight legs that do not fly any of the customers;

minimize how many of the crew members are used to satisfy the flight demands of the plurality of customers;

minimize how many of the aircraft are used to satisfy the flight demands of the plurality of customers;

maximize customer lifetime value; and

minimize delays; and

wherein the one or more objectives of the improvement algorithm may include minimize changes to the schedule constructed using the construction algorithm.

4 . The method of claim 1 , wherein the using the improvement algorithm to modify a portion of the schedule comprises one or more of the following:

identifying a replacement aircraft to replace one of the aircraft that became at least one of grounded, delayed, or infeasible;

identifying a replacement crew member to replace one of the crew members that became unavailable;

assigning an aircraft that had previously been unavailable to an aircraft route;

assigning a crew member that had previously been unavailable to an aircraft route or one or more flight legs thereof;

canceling an aircraft route or one or more flight legs thereof that became unnecessary;

canceling an assignment for at least one of the crew members that became unnecessary;

swapping assignments for at least some of the crew members;

swapping assignments for at least some of the aircraft; or

assigning at least one of the flight demands for at least one of the customers to at least one third party aircraft.

5 . The method of claim 1 , further comprising:

after the construction algorithm has been used to construct the schedule for the one or more specific days in the future, and at least the specified temporal period prior to at least one of the one or more specific days in the future, causing providing to each respective customer of the plurality of customers respective information about the respective flight leg that has been scheduled to fly the customer from the respective departure location to the respective destination location on at least one of the one or more specific days; and

after the improvement algorithm has been used to modify a portion of the schedule, causing providing to each respective customer whose respective flight leg has been changed as a result of the using the improvement algorithm, respective updated information about an updated respective flight leg that has been scheduled to fly the customer from the respective departure location to the respective destination location on at least one of the one or more specific days.

6 . The method of claim 5 , further comprising:

after the construction algorithm has been used to construct the schedule for the one or more specific days in the future, and at least the specified temporal period prior to at least one of the one or more specific days in the future, causing providing, to each respective crew member of the plurality of crew members that are included on the schedule, information about the respective aircraft route or one or more flight legs thereof to which the crew member has been assigned; and

after the improvement algorithm has been used to modify a portion of the schedule, causing providing to each respective crew member of the plurality of crew members whose respective aircraft route or one or more flight legs thereof has been changed as a result of the using the improvement algorithm, respective updated information about an updated aircraft route or one or more flight legs thereof to which the crew member has been assigned.

7 . The method of claim 1 , further comprising:

at multiple times preceding the specified temporal period prior to the one or more specific days, between which times the demand information and the supply information are updated, using the construction algorithm to construct prior versions of the schedule for the one or more specific days in the future and causing displaying of at least a portion of one or more of the prior versions of the schedule to a representative of the on-demand private aviation operator along with information related to the one or more objectives of the construction algorithm; and

allowing the representative of the on-demand private aviation operator to lock-in one or more portions of one or more prior versions of the schedule such that the one or more portions that are locked-in by the representative of the on-demand private aviation operator are included in the schedule for the one or more specific days in the future.

8 . The method of claim 1 , wherein the constraints related to the aircraft, the crew members, and the customers include hard constraints and optionally also include one or more soft constraints.

9 . The method of claim 1 , wherein the specified criterion comprises at least one of the following:

no further NCC is identified; or

an iterative improvement provided by a most recently identified NCC is below a specified threshold.

10 . The method of claim 1 , wherein the specified criterion comprises at least one of the following:

a specified number of iterations of the neighborhood search have already occurred; or

a specified time limit for performing the neighborhood search has already occurred.

11 . A system for constructing and modifying a schedule for an on-demand private aviation operator, the system comprising:

a data store that stores demand information and supply information,

the demand information including a respective flight demand for each customer of a plurality of customers that have requested to fly from a respective departure location to a respective destination location departing at a respective time and day of one or more specific days in the future, and

the supply information including a respective availability for each of a plurality of aircraft and for each of a plurality of crew members on the one or more specific days in the future;

one or more processors interfaced with the data store and configured to:

construct a schedule, using a construction algorithm, for the one or more specific days in the future that satisfies the flight demands of the customers and optimizes the schedule to achieve one or more objectives of the construction algorithm while complying with constraints related to the aircraft, the crew members, and the customers;

wherein the schedule constructed using the construction algorithm assigns respective aircraft to respective aircraft routes each of which includes one or more flight legs, and assigns respective crew members to the respective aircraft routes or one or more of the flight legs thereof; and

wherein each said flight leg of each said aircraft route may be used to satisfy at least a portion of a said flight demand of a said customer; and

on one of the one or more specific days or within a specified temporal period prior thereto, in response to receiving an indication of a change to at least one of the supply information or the demand information that warrants a modification to the schedule, use an improvement algorithm that differs from the construction algorithm to modify a portion of the schedule to achieve one or more objectives of the improvement algorithm while complying with the constraints related to the aircraft, the crew members, and the customers;

wherein to use of the improvement algorithm to modify the portion of the schedule to achieve the one or more objectives of the improvement algorithm while complying with the constraints related to the aircraft, the crew members, and the customers, the one or more processors are configured to:

construct a graph data model by

generating an initial feasible solution (IFS) that can be used to satisfy a said flight demand for a said customer that is in recovery because of the change to at least one of the supply information or the demand information that warrants the modification to the schedule; and

creating and populating node layers and nodes of a graph data model corresponding to the IFS and constructing arcs between different ones of the nodes included in different ones of the node layers, such that: each of the nodes in the graph data model corresponds to a respective flight demand, each of the node layers in the graph data model corresponds to a respective aircraft route that can be used to satisfy one or more of the flight demands, one of the nodes in the graph data model corresponds to the said flight demand that is in recovery, one of the node layers in the graph data model corresponds to an aircraft route that can be used to satisfy the said flight demand that is in recovery, and the arcs in the graph data model define links between pairs of the nodes included in different ones of the node layers;

perform a neighborhood search on the graph data model, which includes iteratively identifying improvements in the graph data model by iteratively identifying one or more negative cost cycles (NCCs) until a specified criterion is satisfied; and

modify the portion of the schedule, based on results of the neighborhood search performed on the graph data model, to achieve the one or more objectives of the improvement algorithm while complying with the constraints related to the aircraft, the crew members, and the customers.

12 . The system of claim 11 , wherein to use the construction algorithm to construct the schedule for the one or more specific days in the future, the one or more processors are configured to:

perform route enumeration to produce a list of feasible aircraft routes that can be used to satisfy the flight demands of the plurality of customers on the one or more specific days using those of the plurality of aircraft available on the one or more specific days;

perform route selection to select, from the list of feasible aircraft routes produced as a result of performing the route enumeration, a shortened list of the feasible aircraft routes that can be used to satisfy the flight demands of the plurality of customers on the one or more specific days using those of the plurality of crew members available on the one or more the specific days; and

perform route optimization to select, from the shortened list of the feasible aircraft routes, a respective single aircraft route for each of the aircraft included in the schedule, respective crew members for each of the respective flight legs, and a respective single flight leg for each of the flight demands of the plurality of customers,

wherein the route optimization optimizes the schedule to achieve the one or more objectives of the construction algorithm while complying with the constraints related to the aircraft, the crew members, and the customers.

13 . The system of claim 12 , wherein the one or more objectives of the construction algorithm include one or more of the following:

maximize revenues;

minimize costs;

maximize profits;

minimize flight legs that do not fly any of the customers;

minimize how many of the crew members are used to satisfy the flight demands of the plurality of customers;

minimize how many of the aircraft are used to satisfy the flight demands of the plurality of customers;

maximize customer lifetime value; and

minimize delays; and

wherein the one or more objectives of the improvement algorithm may include minimize changes to the schedule constructed using the construction algorithm.

14 . The system of claim 11 , wherein to use the improvement algorithm to modify a portion of the schedule, the one or more processors are configured to do one or more of the following:

identify a replacement aircraft to replace one of the aircraft that became at least one of grounded, delayed, or infeasible;

identify a replacement crew member to replace one of the crew members that became unavailable;

assign an aircraft that had previously been unavailable to an aircraft route;

assign a crew member that had previously been unavailable to an aircraft route or one or more flight legs thereof;

cancel an aircraft route or one or more flight legs thereof that became unnecessary;

cancel an assignment for at least one of the crew members that became unnecessary;

swap assignments for at least some of the crew members;

swap assignments for at least some of the aircraft; or

assign at least one of the flight demands for at least one of the customers to at least one third party aircraft.

15 . The system of claim 11 , wherein the one or more processors are further configured to:

after the construction algorithm has been used to construct the schedule for the one or more specific days in the future, and at least the specified temporal period prior to at least one of the one or more specific days in the future, cause to be provided to each respective customer of the plurality of customers respective information about the respective flight leg that has been scheduled to fly the customer from the respective departure location to the respective destination location on at least one of the one or more specific days; and

after the improvement algorithm has been used to modify a portion of the schedule, cause to be provided to each respective customer whose respective flight leg has been changed as a result of the using the improvement algorithm, respective updated information about an updated respective flight leg that has been scheduled to fly the customer from the respective departure location to the respective destination location on at least one of the one or more specific days.

16 . The system of claim 15 , wherein the one or more processors are further configured to:

after the construction algorithm has been used to construct the schedule for the one or more specific days in the future, and at least the specified temporal period prior to at least one of the one or more specific days in the future, cause to be provided to each respective crew member of the plurality of crew members that are included on the schedule, information about the respective aircraft route or one or more flight legs thereof to which the crew member has been assigned; and

after the improvement algorithm has been used to modify a portion of the schedule, cause to be provided to each respective crew member of the plurality of crew members whose respective aircraft route or one or more flight legs thereof has been changed as a result of the using the improvement algorithm, respective updated information about an updated aircraft route or one or more flight legs thereof to which the crew member has been assigned.

17 . The system of claim 11 , wherein the one or more processors are further configured to:

at multiple times preceding the specified temporal period prior to the one or more specific days, between which times the demand information and the supply information are updated, use the construction algorithm to construct prior versions of the schedule for the one or more specific days in the future and causing displaying of at least a portion of one or more of the prior versions of the schedule to a representative of the on-demand private aviation operator along with information related to the one or more objectives of the construction algorithm; and

allow the representative of the on-demand private aviation operator to lock-in one or more portions of one or more prior versions of the schedule such that the one or more portions that are locked-in by the representative of the on-demand private aviation operator are included in the schedule for the one or more specific days in the future.

18 . The system of claim 11 , wherein the constraints related to the aircraft, the crew members, and the customers include hard constraints and optionally also include one or more soft constraints.

19 . The system of claim 11 , wherein the specified criterion comprises at least one of the following:

no further NCC is identified; or

an iterative improvement provided by a most recently identified NCC is below a specified threshold.

20 . The system of claim 11 , wherein the specified criterion comprises at least one of the following:

a specified number of iterations of the neighborhood search have already occurred; or

a specified time limit for performing the neighborhood search has already occurred.

21 . A non-transitory computer readable medium comprising a plurality of instructions stored thereon and executable by at least one processor, the plurality of instructions for constructing and modifying a schedule for an on-demand private aviation operator, the plurality of instructions comprising:

instructions for at least one of obtaining or accessing demand information including a respective flight demand for each customer of a plurality of customers that have requested to fly from a respective departure location to a respective destination location departing at a respective time and day of one or more specific days in the future;

instructions for at least one of obtaining or accessing supply information including a respective availability for each of a plurality of aircraft and for each of a plurality of crew members on the one or more specific days in the future;

instructions for using a construction algorithm to construct a schedule for the one or more specific days in the future that satisfies the flight demands of the customers and optimizes the schedule to achieve one or more objectives of the construction algorithm while complying with constraints related to the aircraft, the crew members, and the customers;

wherein the schedule constructed using the construction algorithm assigns respective aircraft to respective aircraft routes each of which includes one or more flight legs, and assigns respective crew members to the respective aircraft routes or one or more of the flight legs thereof; and

wherein each said flight leg of each said aircraft route may be used to satisfy at least a portion of a said flight demand of a said customer; and

instructions for, on one of the one or more specific days or within a specified temporal period prior thereto, receiving an indication of a change to at least one of the supply information or the demand information that warrants a modification to the schedule, and in response thereto, using an improvement algorithm that differs from the construction algorithm to modify a portion of the schedule to achieve one or more objectives of the improvement algorithm while complying with the constraints related to the aircraft, the crew members, and the customers;

wherein the instructions for using the improvement algorithm to modify the portion of the schedule to achieve the one or more objectives of the improvement algorithm while complying with the constraints related to the aircraft, the crew members, and the customers, includes instructions for:

constructing a graph data model by

generating an initial feasible solution (IFS) that can be used to satisfy a said flight demand for a said customer that is in recovery because of the change to at least one of the supply information or the demand information that warrants the modification to the schedule; and

creating and populating node layers and nodes of a graph data model corresponding to the IFS and constructing arcs between different ones of the nodes included in different ones of the node layers, such that: each of the nodes in the graph data model corresponds to a respective flight demand, each of the node layers in the graph data model corresponds to a respective aircraft route that can be used to satisfy one or more of the flight demands, one of the nodes in the graph data model corresponds to the said flight demand that is in recovery, one of the node layers in the graph data model corresponds to an aircraft route that can be used to satisfy the said flight demand that is in recovery, and the arcs in the graph data model define links between pairs of the nodes included in different ones of the node layers;

performing a neighborhood search on the graph data model, which includes iteratively identifying improvements in the graph data model by iteratively identifying one or more negative cost cycles (NCCs) until a specified criterion is satisfied; and

modifying the portion of the schedule, based on results of the neighborhood search performed on the graph data model, to achieve the one or more objectives of the improvement algorithm while complying with the constraints related to the aircraft, the crew members, and the customers.

Assignments (2)

References Cited (21)