Applying Constraint Programming to Identification and Assignment of Service Professionals
Today many companies face the challenge of matching highly-skilled professionals to high-end positions in large organizations and human deployment agencies. Non-accurate matches in these businesses can result in significant monetary losses and other negative effects. Unlike traditional Workforce Management (WM) problems such as shift scheduling, highly-skilled employees are professionally distinguishable from each other and hence non-interchangeable. Therefore, the techniques used for shift-scheduling can’t be applied to the highly-skilled WM domain. Our work focuses on providing a Constraint Programming solution for supporting the assignment of highly-skilled professionals. Our experience shows that CP is well adapted to this problem. CP supports very well the underlying constraints. In addition, the rich expressive language supported by CP allows us to provide a convenient mechanism for changing and adding new matching and preference constraints. Based on this technology, we have built a tool that is currently being used by IBM service organizations and provides strong business results.
KeywordsConstraint Programming Feasibility Problem Assignment Mode Shift Schedule Preference Rule
Unable to display preview. Download preview PDF.
- 1.Naveh, Y., Rimon, M., Jaeger, I., Katz, Y., Vinov, M., Marcus, E., Shurek, G.: Constraint-based random stimuli generation for hardware verification. AI Magazine 28, 13–30 (2007)Google Scholar
- 3.Richter, Y., Naveh, Y., Gresh, D.L., Connors, D.P.: Optimatch: Applying constraint programming to workforce management of highly-skilled employees. In: IEEE/INFORMS International Conference on Service Operations and Logistics, and Informatics (SOLI), pp. 173–178 (2007)Google Scholar
- 4.Gilat, D., Landau, A., Ribak, A., Shiloach, Y., Wasserkrug, S.: Swops– shift work optimized planning and scheduling. In: Proc. 6th International Conference on the Practice and Theory of Automated Timetabling (PATAT), pp. 518–523 (2006)Google Scholar
- 6.Munaf, D., Tester, B.: And/or parallel programming in practice. Technical Report WP12:1203, British Telecom Research Lab, London, UK (1993)Google Scholar
- 7.Yang, R.: Solving a workforce management problem with constraint programming. In: The 2nd International Conference on the Practical Application of Constraint Technology, pp. 373–387 (1996)Google Scholar
- 10.van Hentenryck, P.: The OPL optimization programming language, Cambridge, MA, USA (1999)Google Scholar
- 11.Dechter, R.: Constraint Processing. Elsevier Scinece, Amsterdam (2003)Google Scholar