Spatio-temporal approach to scheduling field operations

Patent metadata

Field	Value
Publication number	US-12499395-B2
Application number	US-202318523785-A
Country	US
Kind code	B2
Filing date	Nov 29, 2023
Priority date	Mar 15, 2013
Publication date	Dec 16, 2025
Grant date	Dec 16, 2025

Abstract

A method for creating a spatio-temporal schedule includes receiving a set of available work crews and a set of workorders to be scheduled, sequencing the set of workorders, wherein each workorder of the set of workorders is associated with a geographic location, a start time and an end time, and iterating through the set of available work crews, assigning a plurality of workorders of the set of workorders fully allocating a current crew before selecting a next crew, until all work crews are fully allocated and/or all workorders are assigned, wherein the assignment of workorders for a given work crew generates a route comprising the plurality of workorders.

First claim

What is claimed is:

1 . A method for creating a spatio-temporal schedule comprising:
receiving a set of workorders, each workorder of the set of workorders including a start time, an end time, task location, and one of a plurality of field services on an asset; receiving, from a user, a selection of a plurality of objectives; preprocessing, by a processor, the set of workorders and the plurality of objectives, thereby generating preprocessed data; providing, by the processor, the preprocessed data to a data model, the data model comprising a set of computer programming language classes; determining, by the processor based on the preprocessed data and the data model, a sequence of the set of workorders, the determining being subject to: maximizing the plurality of selected objectives and the data model, the plurality of selected objectives including sequencing each of the set of workorders based on a priority of the workorder, completion time of a supercrew of all of the set of workorders, travel time between workorders, and a number of assigned workorders, constraints of the data model including a guarantee that all workorders of the set of workorders are sequenced, there is no overlap in the sequence of workorders, the travel times for at least one work crew, and a requirement that all work crews of the supercrew start at a specified location, the supercrew comprising a set of available work crews; identifying, by the processor, equipment for at least one of or more of the workorders located at the one least one task location; and iterating, by the processor, through the set of available work crews, for each of the work crews of the set of available work crews:
assigning, by the processor, successive ones of the sequence of the set of workorders to a current work crew of the set of available work crews until the current work crew is fully allocated before selecting a next work crew;
identifying, by the processor based on an output of the data model using the preprocessed data as input for the data model, geographic routes for each current work crew based on assignments;
determining, by the processor, a first utilization of the current work crew, the determination of the first utilization being a ratio of a total work time for the current work crew divided by a total time spent for the current work crew, the total time spent for the current work crew including travel time between successive workorders of the sequence of the set of workorders for the current work crew; and
outputting, by the processor, to an interface, at least one of the geographic routes for each of the work crews and an icon for each task location associated with the workorder along the at least one of the geographic routes, the interface further depicting the identified equipment for the at least one or more of the workorders located at the at least one task location and depicting the sequence of the set of workorders for each of the work crews of the set of available work crews along the at least one of the geographic routes, thereby improving up-times of the assets in a field by efficient scheduling of field services.

2 . The method of claim 1 further comprising: receiving a maximum time limit to determine the sequence of the set of workorders.

3 . The method of claim 1 further comprising if the first utilization of the current work crew is less than an alpha-weighted average of other work crews of the set of available work crews:
removing all work orders assigned to the current work crew from the current work crew;
determining a new sequence of unassigned workorders of the set of workorders, the determining being subject to maximizing the plurality of selected objectives and the constrained data model;
assigning successive ones of the new sequence of unassigned workorders to the current work crew of the set of available work crews until the current work crew is fully allocated;
determining a second utilization of the current work crew;
comparing the second utilization to the alpha-weighted average of other work crews of the set of available work crews; and
if the second utilization is greater than the alpha-weighted average of other work crews, then the current work crew is removed from a list of available work crews.

4 . The method of claim 1 further comprising if the first utilization of the current work crew is greater than an alpha-weighted average of other work crews, then the current work crew is removed from a list of available work crews.

5 . The method of claim 1 , wherein maximizing the plurality of selected objectives is maximizing a sum of the priority of each of the workorders in the set of workorders.

6 . The method of claim 1 , wherein maximizing the plurality of selected objectives is maximizing a sum of a duration of each of the workorders in the set of workorders.

7 . The method of claim 1 , wherein maximizing the plurality of selected objectives is minimizing a sum of a distance travelled by each of the work crews of the set of available work crews.

8 . A system comprising:
one or more processors; and memory containing instructions to control the one or more processors to:
receive a selection of a plurality of objectives;
preprocess, by the one or more processors, the set of workorders and the plurality of objectives, thereby generating preprocessed data;
provide, by the one or more processors, the preprocessed data to a data model, the data model comprising a set of computer programming language classes;
determine, by the one or more processors based on the preprocessed data and the data model, a sequence of the set of workorders, the determining being subject to: maximizing the plurality of selected objectives and the data model, the plurality of selected objectives including sequencing each of the set of workorders based on a priority of the workorder, completion time of a supercrew of all of the set of workorders, travel time between workorders, and a number of assigned workorders, constraints of the data model including a guarantee that all workorders of the set of workorders are sequenced, there is no overlap in the sequence of workorders, the travel times for at least one work crew, and a requirement that all work crews of the supercrew start at a specified location, the supercrew comprising a set of available work crews;
identify, by the one or more processors, equipment for at least one of or more of the workorders located at the one least one task location; and
iterate, by the one or more processors, through the set of available work crews, for each of the work crews of the set of available work crews:
assign, by the one or more processors, successive ones of the sequence of the set of workorders to a current work crew of the set of available work crews until the current work crew is fully allocated before selecting a next work crew;
identify, by the one or more processors based on an output of the data model using the preprocessed data as input for the data model, geographic routes for each current work crew based on assignments;
determine, by the one or more processors, a first utilization of the current work crew, the determination of the first utilization being a ratio of a total work time for the current work crew divided by a total time spent for the current work crew, the total time spent for the current work crew including travel time between successive workorders of the sequence of the set of workorders for the current work crew; and
output, by the one or more processors, to an interface, at least one of the geographic routes for each of the work crews and an icon for each task location associated with the workorder along the at least one of the geographic routes, the interface further depicting the identi

Assignees

• Utopus Insights Inc

Inventors

• Candas Mehmet F
• Hampapur Arun
• Kumar Tarun
• Mahatma Shilpa N

Classifications

• G06Q10/047

  Optimisation of routes or paths, e.g. travelling salesman problem · CPC title

• G06Q10/06313 Primary

  Resource planning in a project environment · CPC title