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REPORT DATE (DD-MM-YYYY)
05-01-2011
REPORT TYPE
7184D214
PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT NUMBERThe University of Texas at San Antonio One UTSA Circle San Antonio TX 78249
SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR'S ACRONYM(S)Air
SPONSOR/MONITOR'S REPORT NUMBER(S)AFRL-RH-WP-TR-2011-0019
DISTRIBUTION / AVAILABILITY STATEMENTDistribution A: Approved for public release; distributed is unlimited.
SUPPLEMENTARY NOTES88ABW/PA cleared on 23 Feb 2011, 88ABW-2011-0727.
ABSTRACTThe main objective of this project is to enhance the effectiveness of workforce forecast and deployment through innovative approaches of artificial intelligence. The research included a final document of conventional and innovative methods of workforce forecasting and a decision support software program incorporating advanced artificial intelligence techniques for workforce forecasting.
SUBJECT TERMS
ABSTRACTThis project studies workforce forecasting in two main aspects: (1) an extensive review of the existing methodologies and techniques and (2) an effort to develop a decision support system with models and software programming. The main objective of this project is to enhance the effectiveness of workforce forecasting and deployment through innovative approaches of artificial intelligence. The deliverables include a summary report of conventional and innovative methods of workforce forecasting (Part I) and a decision support software program using artificial intelligence techniques for workforce forecasting (Part II).Part I, provided a thorough literature review of fundamental research and practices of demand and supply forecasting techniques for workforce analysis. Over 300 relevant literatures have been identified and reviewed by the project team, and 289 of them are covered in this report.Following is a summary of the main contents and contributions of Part I:• This report provides an extensive review of the fundamental knowledge, applications, guidelines, and scope of use of various workforce forecasting methods.• A decision tree has been proposed for selecting an appropriate forecasting ...