Systems and methods for resource allocation for management systems

• US 10,362,139 B2
• Filed: 10/06/2016
• Issued: 07/23/2019
• Est. Priority Date: 10/06/2016
• Status: Active Grant

• Current Assignee: Mitsubishi Electric Research Laboratories, Inc. (Mitsubishi Electric Corporation)
• Original Assignee: Mitsubishi Electric Research Laboratories, Inc. (Mitsubishi Electric Corporation)
• Inventors: Raghunathan, Arvind, Bergman, David, Sahinidis, Nikolaos V.
• Primary Examiner(s): Shingles, Kristie D
• Application Number:
  US15/286,712
• Publication Number:
  US 20180103116A1
• Time in Patent Office: 1,020 Days
• Field of Search: 709224
• CPC Class Codes: H04L 67/01 Protocols
• CPC Class Codes: H04L 67/10 in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04L 67/60 Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources admission control or resource allocation H04L47/70

Abstract

Methods and systems for servicing of machines by workers within a period of time. Acquiring for each service an available servicing time, a time duration for servicing, a location of the machine, and a number of workers having appropriate qualifications to be concurrently present for a service. Acquiring for each worker a worker availability, qualifications and location. Determining a cost function representing a service schedule for each worker, wherein an optimization of the cost function is subject to constraints. The constraints include a number of workers with qualifications concurrently present for a service, each worker starts and ends the period of time at the same location and travels independently from other workers. The cost function includes maximizing a number of services to be performed; minimizing a number of workers required to perform servicing for each service; or minimizing a total travel time for each worker to the location.

Claims

1. A method facilitating servicing of a plurality of machines by one or more worker within a specific period of time, each worker includes a combination of qualifications and located at one or more service center, comprising:

acquiring machine service information via at least one user input interface, for each service, by a computer in communication with the at least one user input interface, the computer having a tangible computer readable recordable medium containing stored program instructions executable by the computer;

acquiring worker information, for each worker, by the computer, wherein the working information associated with each worker comprises the worker'"'"'s types of transportation modes available at the assigned worker'"'"'s service center location in the scheduling process;

acquiring constraints to be applied to a cost function, by the computer, the constraints include a specified number of workers with qualifications that are concurrently present for a specific service, each worker starts and ends the specific period of time at the same location and travels independently from other workers and each service needs to be performed within the specific period within the predetermined time window; and

determining the cost function representing a service schedule for each worker for the specific period of time, wherein an optimization of the cost function is subject to the constraints, such as assigning of services to each worker and routing of each worker based upon a sequence in which the services are to be performed, and the worker'"'"'s types of transportation modes available at the assigned worker'"'"'s service center location in the scheduling process, such that if the constraints cannot verify at least one acceptable solution, then a user via the at least one user interface imposes additional constraints, otherwise, when the constraints verify the at least one acceptable solution and the cost function includes one or combination of;

maximizing a number of services to be performed by each worker;

minimizing a number of workers required to perform servicing for each service;

a minimum cumulative risk of component failure or minimizing a total travel time for each worker to the location to be serviced.

2. The method of claim 1, further comprising:

receiving a user input on a surface of the at least one user input interface, wherein the user input relates to a service non-completion for a machine within the scheduled period of time, and processing the user input to determine a revised change in the time duration for servicing the machine, along with a revised change in the specified number of workers having appropriate qualifications to be concurrently present for the specific service to be performed; and

repeating the determining and the optimizing step after receiving the user input, until a revised service schedule for each worker is produced for another specific period of time.

3. The method of claim 1, wherein the machine service information includes an available period of time to perform servicing of a machine, an available predetermined time window to perform servicing the machine, a time duration for servicing of the machine, a location of the machine, and a specified number of workers having appropriate qualifications to be concurrently present for a specific service to be performed.

4. The method of claim 1, wherein the worker information includes an availability of the worker to perform servicing, qualifications of the worker and location of the worker.

5. The method of claim 1, further comprising:

receiving a user input on a surface of the at least one user input interface to set a user time-limit for determining the service schedule, and processing the user input to determine if the user time-limit is met.

6. The method of claim 1, wherein a constraint programming algorithm is used to solve the optimization of the cost function or a mixed integer programming algorithm is used to solve the optimization of the cost function.

7. The method of claim 1, wherein a mixed integer programming algorithm is used in combination with a constraint programming algorithm to solve the optimization of the cost function.

8. The method of claim 7, wherein the mixed integer programming algorithm is used to solve for:

determining a set of services to be performed within the specific period of time and within the available predetermined time window for servicing each machine, and then,

determining a set of available and qualified workers to perform the servicing for each service within the specific period of time and within the available predetermined time window for servicing each machine.

9. The method of claim 8, wherein after the mixed integer programming algorithm has determined the set of services to be performed within the specific period of time and the set of available and qualified workers, to perform the servicing for each service within the specific period of time, then the constraint programming algorithm is used to solve for:

determining a service sequencing, in which, the set of services are to be performed within the specific period of time, based upon the available predetermined time window for servicing each machine and the set of available and qualified workers, and then,

assigning each worker, a sequence in which the services are performed, subject to obtaining a feasible solution, if the feasible solution is not obtained, then add a constraint to invalidate this assignment of services to the worker, and repeat the mixed integer programming algorithm, until the feasible solution is obtained,

so as to determine the maximize number of services to be performed within the specific period of time.

10. The method of claim 1, wherein the plurality of machines are elevators.

11. The method of claim 10, further comprising:

acquiring, for each service, historical elevator servicing data of the elevator being serviced,

determining if components of the elevator have been serviced within each component'"'"'s predetermined servicing time-limit, for each component not serviced within the component'"'"'s predetermined servicing time-limit, a penalty point is assigned per each service of the elevator,

evaluating each component'"'"'s assigned total penalty points, and comparing the total penalty points to a threshold specifically set for each component, such that if the total penalty points are above the threshold, priority is given to servicing the elevator over other services in the next specific period of time for servicing the plurality of elevators.

12. The method of claim 11, wherein the penalty point is based upon the component of the failure probability times the impact of failure and the threshold is an estimated measure of a risk of failure of the component.

13. The method of claim 1, wherein the additional constraints include one of complex constraints, constraints revealed to the user after a solution has been accepted or constraints that need to be modified to render the problem feasible.

14. A system facilitating servicing a plurality of machines by a plurality of workers, comprising:

at least one user input interface to accept machine service information and worker information, wherein the working information associated with each worker comprises the worker'"'"'s types of transportation modes available at the assigned worker'"'"'s service center location in the scheduling process; and

a computer having a computer readable recordable memory and in communication with the at least one user input interface, and has stored therein program instructions executable by the computer, wherein the computer also includes stored constraints to be applied to a cost function, the constraints include a specified number of workers with qualifications that are concurrently present for a specific service, each worker starts and ends the specific period of time at the same location and travels independently from other workers and each service needs to be performed within the specific period within the predetermined time window;

wherein the computer is configured to;

determine the cost function representing a service schedule for each worker for the specific period of time, wherein an optimization of the cost function is subject to the constraints, such as assigning of services to each worker and routing of each worker based upon a sequence in which the services are to be performed, and the worker'"'"'s types of transportation modes available at the assigned worker'"'"'s service center location in the scheduling process, such that the cost function includes one or combination of;

maximize a number of services to be performed by each worker;

minimize a number of workers required to perform servicing for each service;

a minimum cumulative risk of component failure or minimize a total travel time for each worker to the location to be serviced; and

at least one output interface for rendering to the worker a corresponding service schedule.

15. The system of claim 14, further comprising:

a user input is provided on a surface of the at least one user input interface and received by the computer, wherein the user input relates to a service non-completion for a machine within the scheduled period of time, and processing the user input to determine a revised change in the time duration for servicing the machine, along with a revised change in the specified number of workers having appropriate qualifications to be concurrently present for the specific service to be performed; and

repeat the determining and the optimizing step after receiving the user input, until a revised service schedule for each worker is produced for another specific period of time.

16. The system of claim 14, wherein the machine service information includes an available period of time to perform servicing of a machine, an available predetermined time window to perform servicing the machine, a time duration for servicing of the machine, a location of the machine, and a specified number of workers having appropriate qualifications to be concurrently present for a specific service to be performed and the worker information includes an availability of the worker to perform servicing, qualifications of the worker and location of the worker.

17. The system of claim 14, wherein the optimization of the cost function is subject to the constraints, such that the constraints reduce an amount of determinable variable values while determining the service schedule, which results in a reduced amount of data processed, and in turn reduces an amount of processing time by the computer.

18. The system of claim 14, wherein a mixed integer programming algorithm is used in combination with a constraint programming algorithm to solve the optimization of the cost function.

19. The system of claim 18, wherein the mixed integer programming algorithm is used to solve for:

determining a set of services to be performed within the specific period of time and within the available predetermined time window for servicing each machine, and then,

determining a set of available and qualified workers to perform the servicing for each service within the specific period of time and within the available predetermined time window for servicing each machine.

20. The system of claim 19, wherein after the mixed integer programming algorithm has determined the set of services to be performed within the specific period of time and the set of available and qualified workers, to perform the servicing for each service within the specific period of time, then the constraint programming algorithm is used to solve for:

determining a service sequencing, in which, the set of services are to be performed within the specific period of time, based upon the available predetermined time window for servicing each machine and the set of available and qualified workers, and then,

assigning each worker a sequence in which the services are performed, subject to obtaining a feasible solution, if the feasible solution is not obtained, then add a constraint to invalidate this assignment of services to the worker, and repeat the mixed integer programming algorithm, until the feasible solution is obtained,

so as to determine the maximize number of services to be performed within the specific period of time.