Donald Samuels, Ian Stobert
SPIE Photomask Technology + EUV Lithography 2007
Today many companies face the challenge of matching highly skilled professionals to high-end positions in large organisations and human deployment agencies. Unlike traditional workforce management problems, such as shift scheduling, highly skilled employees are professionally distinguishable from each other and hence non-interchangeable. Our work specifically focuses on the services industry, where much of the revenue comes from the assignment of highly professional workers. Here, non-accurate matches may result in significant monetary losses and other negative effects. We deal with very large pools of both positions and employees, where optimal decisions should be made rapidly in a dynamic environment. Since traditional operations research methods fail to answer this problem, we employ Constraint Programming (CP), a subfield of Artificial Intelligence with strong algorithmic foundations. Our CP model builds on new constraint propagators designed for this problem (but applicable elsewhere), as well as on information retrieval methods used for analysing the complex text describing high-end professionals and positions. Optimatch, which is based on this technology and is being used by IBM services organisations, provides strong experimental results. © 2008, Inderscience Publishers.
Donald Samuels, Ian Stobert
SPIE Photomask Technology + EUV Lithography 2007
Elena Cabrio, Philipp Cimiano, et al.
CLEF 2013
G. Ramalingam
Theoretical Computer Science
Marshall W. Bern, Howard J. Karloff, et al.
Theoretical Computer Science