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

摘要

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%.