A Multi-Objective Approach to a Bipartite Assignment Matching Problem Using Weighted Values from Multiple Contraints

Abstract

US Air Force recruiters routinely assign new recruits to available jobs every month. The goal is to find the best assignments in an efficient manner. Although this problem is modeled as a bipartite assignment matching problem, it is not new to the field of Operations Research. This research presents a new approach to solve assignment matching problems given multiple side constraints. Using two multi-criteria optimization techniques, lexicographic optimization and the elastic constraint method, the assignment matching algorithm efficiently produces an optimal solution in a fraction of the time currently spent. This approach is demonstrated in assigning new USAF recruits to available jobs in any given month for the 369th Recruiting Squadron. The current 369th process manually creates assignments and can take weeks to complete, whereas the assignment matching algorithm takes less than two seconds and, on average, shows an increase in user defined goals of at least 15%.

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Document Details

Document Type
Technical Report
Publication Date
Mar 15, 2010
Accession Number
ADA517411

Entities

People

  • Greg S. Jeong

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Biomedical
  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • African Americans
  • Air Force
  • Algorithms
  • Basic Programming Language
  • Computer Programming
  • Data Analysis
  • Department Of Defense
  • Goal Programming
  • Military Organizations
  • Multiobjective Optimization
  • Operating Systems
  • Operations Research
  • Optimization
  • Recruiting
  • Recruits
  • Spreadsheet Software
  • Squadrons

Readers

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