Methods and apparatus for allocating resources in the presence of uncertainty

• US 6,625,577 B1
• Filed: 02/06/2001
• Issued: 09/23/2003
• Est. Priority Date: 01/21/1999
• Status: Expired due to Fees

• Current Assignee: Joel Jameson
• Original Assignee: Joel Jameson
• Inventors: Jameson, Joel
• Primary Examiner(s): Hayes, John W
• Application Number:
  US09/777,336
• Time in Patent Office: 959 Days
• Field of Search: 705/7, 705/8, 705/1, 705/400, 700/36, 700/95, 700/99
• US Class Current: 705/7.25
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/0631 Resource planning, allocation, distributing or scheduling for enterprises or organisations
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 10/0637 Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals

Abstract

A method of allocating resources in the presence of uncertainty is presented. The method builds upon deterministic methods and initially creates and optimizes scenarios. The invention employs clustering, line-searching, statistical sampling, and unbiased approximation for optimization. Clustering is used to divide the allocation problem into simpler sub-problems, for which determining optimal allocations is simpler and faster. Optimal allocations for sub-problems are used to define spaces for line-searches; line-searches are used for optimizing allocations over ever larger sub-problems. Sampling is used to develop Guiding Beacon Scenarios that are used for generating and evaluating allocations. Optimization is made considering both constraints, and positive and negative ramifications of constraint violations. Applications for capacity planning, organizational resource allocation, and financial optimization are presented.

Claims

1. A computer system for optimally allocating organizational resources comprising:

means for obtaining at least two scenarios;

means for obtaining at least a first-stage allocation for at least two of said scenarios; and

means for determining an Optimal Final Allocation including;

means for separately optimizing said first-stage allocations against each scenario such that said optimizing means generates additional stage allocations,

means for re-optimizing the additional stage allocations against each scenario, and

means for resolving infeasibilities that may occur during said means for optimizing and said means for re-optimizing.