Tactical Resource Planner for Workforce Allocation in Telecommunications

  • Ahmed Mohamed
  • Hani Hagras
  • Sid Shakya
  • Gilbert Owusu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7326)


Resource planning is one of the most important operational issues for many companies. This is especially crucial for telecommunications companies. Resource planning aims to provide a high quality of service to the customers while trying to keep the cost as low as possible. This is done by trying to utilize the available resources (workforce) as much as possible so that they can match the expected demand for services. Tactical resource planning looks at medium-term planning periods, i.e. weeks to months, and aims to establish coarse-grain resource deployments. This paper focuses on fuzzy based resource planning approach in British Telecom (BT). We will present a hierarchical based fuzzy logic system which calculates the compatibility between resources (technicians) and the allocated tasks, and then matches the most compatible tasks and technicians to each other. The proposed hierarchical fuzzy logic based system in an experimental setting was able to achieve very good results in comparison to the original system, where the proposed system was able to achieve 12.2% improvement in utilization, 34% increase in technician deployment ,10.8% decrement in travel time and 116.2% improvement in number of important tasks being completed. The proposed system is being incorporated in the workforce planning system in BT.


fuzzy logic systems hierarchical fuzzy logic systems tactical resource planning and telecommunications 


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  1. 1.
    Kern, M., Shakya, S., Owusu, G.: Integrated Resource Planning for Diverse Workforces. In: Computers & Industrial Engineering (CIE 2009), pp. 1169–1173 (July 2009)Google Scholar
  2. 2.
    Voudouris, C., Owusu, G., Dorne, R., Lesaint, D.: Service Chain Management. Springer (2008)Google Scholar
  3. 3.
    Wang, S., Gong, L., Yan, S.: The allocation optimization of project human resource based on particle swarm optimization algorithm. In: IITA International Conference on Services Science, Management and Engineering (2009)Google Scholar
  4. 4.
    Weng, W., Su, J., Chen, G., Wang, Z.: An approach for all allocation optimization of multi-project human resource based on DEA. In: International Conference on Management and Service Science (2010)Google Scholar
  5. 5.
    Miller, S., Gongora, M., Popova, V.: Optimising resource plans using an interval type-2 fuzzy model. In: Fourth International Workshop on Genetic and Evolutionary Fuzzy Systems, Mieres, Spain (March 2010)Google Scholar
  6. 6.
    Daojin, F.: Research on the comprehensive evaluation of the human resource allocation based on analytic hierarchy process and fuzzy mathematics. In: Second International Conference on Industrial and Information Systems (2010)Google Scholar
  7. 7.
    Feili, H., Khoshdoon, M.: A Fuzzy Optimization Model for Supply Chain Production Planning with Total Aspect of Decision Making. The Journal of Mathematics and Computer Science 2(1), 65–80 (2011)Google Scholar
  8. 8.
    Saffiotti, A.: Fuzzy logic in autonomous robotics: behaviour coordination. In: Proceedings of the 6th IEEE International Conference on Fuzzy Systems, Barcelona, Spain, pp. 573–578 (1997)Google Scholar
  9. 9.
    Wang, D., Zeng, X., Keane, J.: A survey of hierarchical fuzzy systems. International Journal of Computational Cognition 4(1) (March 2006), http://www.ijcc.us

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Ahmed Mohamed
    • 1
  • Hani Hagras
    • 1
  • Sid Shakya
    • 2
  • Gilbert Owusu
    • 2
  1. 1.School of Computer Science and Electronic EngineeringUniversity of EssexColchesterUK
  2. 2.British Telecommunication Adastral ParkMartleshamUK

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