System and method for determining optimal asset configurations while minimizing disruption to existing business operations in a service delivery environment

• US 9,922,298 B2
• Filed: 01/28/2013
• Issued: 03/20/2018
• Est. Priority Date: 12/12/2012
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Dasgupta, Gargi, Desai, Nirmit V., Diao, Yixin, Heching, Aliza R.
• Primary Examiner(s): BOYCE, ANDRE D
• Application Number:
  US13/751,286
• Publication Number:
  US 20140164045A1
• Time in Patent Office: 1,877 Days
• Field of Search: 705 725
• CPC Class Codes: G06Q 10/06313 Resource planning in a project environment

Abstract

A system for determining asset configuration in a service delivery environment, comprises a simulation module developing a simulation model reflecting features of the service delivery environment, a search module using the simulation model and constraint data to determine a plurality of asset configurations for evaluation, a first evaluation module determining a value of each of the asset configurations, and determining the asset configuration of the plurality of asset configurations that yields a value meeting a predetermined objective, and a second evaluation module determining a deviation from a current configuration that would be caused by each of the asset configurations, and determining the asset configuration that yields a lowest deviation of the plurality of asset configurations, wherein the second evaluation module uses the value meeting the predetermined objective from the first evaluation module as a constraint when determining the asset configuration that yields the lowest deviation.

Claims

1. A system for determining asset configuration in a computer-based service delivery environment, comprising:

a simulation module developing a simulation model reflecting features of the service delivery environment;

a constraint module receiving a plurality of constraints and outputting constraint data, wherein the plurality of constraints include a service level target, a limit for control of backlog, and a contractual constraint on resource availability;

a search module using the simulation model and the constraint data to determine a plurality of asset configurations for evaluation, wherein the plurality of asset configurations each comprise a configuration of a plurality of agents, and at least one of a machine configuration and a computer software configuration, and wherein the determining of the plurality of the asset configurations is performed by using at least one metaheuristic mechanism;

a first evaluation module determining a value of each of the asset configurations, and determining the asset configuration of the plurality of asset configurations that yields a value meeting a predetermined objective; and

a second evaluation module determining a deviation from a current configuration that would be caused by each of the asset configurations, and determining the asset configuration that yields a lowest deviation of the plurality of asset configurations, wherein the second evaluation module uses the value meeting the predetermined objective from the first evaluation module as a constraint when determining the asset configuration that yields the lowest deviation;

wherein determining the deviation from the current configuration is based on a weighted number of changes to the current configuration, and the weighted number of the changes is calculated by multiplying a count of the changes to the current configuration by one or more penalties;

wherein determining the value of each of the asset configurations is based on utilization data comprising a percentage of time each agent of the plurality of agents is permitted to work;

wherein the one or more penalties correspond to one or more of the changes determined to result in at least one of a shift change of an agent of the plurality of agents, a relocation of an agent of the plurality of agents, and an altering of which of one or more agents of the plurality of agents interact with an agent of the plurality of agents;

wherein the value of each of the asset configurations is a monetary-based metric, and the deviation from the current configuration is a distance-based metric including a measure of one or more modifications to at least one of a current machine configuration and a current computer software configuration;

wherein the lowest deviation is a solution that minimizes the one or more modifications to at least one of the current machine configuration and the current computer software configuration while meeting the predetermined objective;

wherein the first and second evaluation modules receive simulation model data and the constraint data, and evaluate, via a simulation, whether an asset configuration of the plurality of asset configurations is able to meet the plurality of constraints;

wherein one or more of the modules;

determine whether a stopping criterion has been met;

limit or remove one or more of the plurality of constraints if an asset configuration meeting the plurality of constraints is not found before the stopping criterion has been met; and

continue with determining the value of each of the asset configurations after limiting or removal of one or more of the plurality of constraints; and

wherein the modules are implemented on a computer system comprising a memory and at least one processor coupled to the memory.

2. The system of claim 1, wherein the search module uses at least one of scatter search and tabu search to determine the plurality of asset configurations.

3. The system of claim 1, wherein determining the value of each of the asset configurations is further based on a number of assets in a configuration and uses weighted amounts based on at least one of capabilities and efficiency of the assets.

4. The system of claim 1, wherein the first evaluation module ceases determining the value of each of the asset configurations if the stopping criterion has been met, wherein the stopping criterion is selected from the group consisting of a pre-determined number of asset configurations having been evaluated, a pre-determined period of time has elapsed, and a pre-determined period of time has elapsed since a change of the value meeting the predetermined objective.

5. The system of claim 1, wherein the second evaluation module ceases determining the deviation from the current configuration if the stopping criterion has been met, wherein the stopping criterion is selected from the group consisting of a one of a pre-determined number of asset configurations having been evaluated, a pre-determined period of time has elapsed, and a pre-determined period of time has elapsed since a change of the lowest deviation.

6. The system of claim 1, wherein the second evaluation module outputs an asset configuration solution with the lowest deviation and the value meeting the predetermined objective.

7. The system of claim 1, wherein the features of the service delivery environment reflected in the simulation model include at least one of how work arrives to the service delivery environment, how the work is prioritized, how the work is assigned to and serviced by different assets, and how the work exits the service delivery environment.

8. The system of claim 1, wherein the value meeting the predetermined objective is a cost and the predetermined objective is lowest cost of each of the asset configurations.

9. The system of claim 1, wherein the value meeting the predetermined objective is a profit and the predetermined objective is highest profit of each of the asset configurations.

10. An article of manufacture comprising a non-transitory computer readable storage medium comprising program code tangibly embodied thereon, which when executed by a computer, performs method steps for determining asset configuration in a computer-based service delivery environment, the method steps comprising:

developing a simulation model reflecting features of the service delivery environment;

collecting simulation model data;

collecting constraint data comprising a plurality of constraints for the service delivery environment, wherein the plurality of constraints include a service level target, a limit for control of backlog, and a contractual constraint on resource availability;

using the constraint data to determine a plurality of asset configurations for evaluation, wherein the plurality of asset configurations each comprise a configuration of a plurality of agents, and at least one of a machine configuration and a computer software configuration, and wherein the determining of the plurality of the asset configurations is performed by using at least one metaheuristic mechanism;

evaluating, via a simulation, whether an asset configuration of the plurality of asset configurations is able to meet the plurality of constraints;

determining a value of each of the asset configurations, and determining the asset configuration of the plurality of asset configurations that yields a value meeting a predetermined objective;

determining a deviation from a current configuration that would be caused by each of the asset configurations, and determining, while using the value meeting the predetermined objective as a constraint, the asset configuration that yields a lowest deviation of the plurality of asset configurations; and

identifying a target utilization of each agent of the plurality of agents for use when determining the value of each of the asset configurations, wherein the target utilization comprises a percentage of time each agent of the plurality of agents is permitted to work;

wherein determining the deviation from the current configuration is based on a weighted number of changes to the current configuration, and the weighted number of the changes is calculated by multiplying a count of the changes to the current configuration by one or more penalties;

wherein the one or more penalties correspond to one or more of the changes determined to result in at least one of a shift change of an agent of the plurality of agents, a relocation of an agent of the plurality of agents, and an altering of which of one or more agents of the plurality of agents interact with an agent of the plurality of agents;

wherein the value of each of the asset configurations is a monetary-based metric, and the deviation from the current configuration is a distance-based metric including a measure of one or more modifications to at least one of a current machine configuration and a current computer software configuration;

wherein the lowest deviation is a solution that minimizes the one or more modifications to at least one of the current machine configuration and the current computer software configuration while meeting the predetermined objective; and

wherein the method steps further comprise;

determining whether a stopping criterion has been met; and

limiting or removing one or more of the plurality of constraints if an asset configuration meeting the plurality of constraints is not found before the stopping criterion has been met; and

continuing with determining the value of each of the asset configurations after the limiting or removal of one or more of the plurality of constraints.

11. An apparatus for determining asset configuration in a computer-based service delivery environment, comprising:

a memory; and

a processor coupled to the memory and configured to execute code stored in the memory for;

developing a simulation model reflecting features of the service delivery environment;

collecting simulation model data;

collecting constraint data comprising a plurality of constraints for the service delivery environment, wherein the plurality of constraints include a service level target, a limit for control of backlog, and a contractual constraint on resource availability;

using the constraint data to determine a plurality of asset configurations for evaluation, wherein the plurality of asset configurations each comprise a configuration of a plurality of agents, and at least one of a machine configuration and a computer software configuration, and wherein the determining of the plurality of the asset configurations is performed by using at least one metaheuristic mechanism;

evaluating, via a simulation, whether an asset configuration of the plurality of asset configurations is able to meet the plurality of constraints;

determining a value of each of the asset configurations, and determining the asset configuration of the plurality of asset configurations that yields a value meeting a predetermined objective;

determining a deviation from a current configuration that would be caused by each of the asset configurations, and determining, while using the value meeting the predetermined objective as a constraint, the asset configuration that yields a lowest deviation of the plurality of asset configurations; and

identifying a target utilization of each agent of the plurality of agents for use when determining the value of each of the asset configurations, wherein the target utilization comprises a percentage of time each agent of the plurality of agents is permitted to work;

wherein determining the deviation from the current configuration is based on a weighted number of changes to the current configuration, and the weighted number of the changes is calculated by multiplying a count of the changes to the current configuration by one or more penalties;

wherein the one or more penalties correspond to one or more of the changes determined to result in at least one of a shift change of an agent of the plurality of agents, a relocation of an agent of the plurality of agents, and an altering of which of one or more agents of the plurality of agents interact with an agent of the plurality of agents;

wherein the value of each of the asset configurations is a monetary-based metric, and the deviation from the current configuration is a distance-based metric including a measure of one or more modifications to at least one of a current machine configuration and a current computer software configuration; and

wherein the lowest deviation is a solution that minimizes the one or more modifications to at least one of the current machine configuration and the current computer software configuration while meeting the predetermined objective; and

wherein the processor is further configured to execute code for;

determining whether a stopping criterion has been met; and

limiting or removing one or more of the plurality of constraints if an asset configuration meeting the plurality of constraints is not found before the stopping criterion has been met; and

continuing with determining the value of each of the asset configurations after the limiting or removal of one or more of the plurality of constraints.