Title :
A fuzzy-genetic tactical resource planner for workforce allocation
Author :
Mohamed, Amr ; Hagras, Hani ; Shakya, Sunny ; Owusu, Gilbert
Author_Institution :
Comput. Intell. Centre, Univ. of Essex, Colchester, UK
Abstract :
For the recent few years, resource planning has become an interesting research topic for many companies, especially within telecommunications domain. Resource planning is basically trying to provide a high quality of service while trying to keep the cost as low as possible. The main aim of resource planning is to utilize the available resources 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. In our previous work we introduced an experimental fuzzy based resource planning approach modeled for a delivery unit in British Telecom (BT) [1]. We presented a hierarchical based fuzzy logic system, which calculates the compatibility between resources and the allocated tasks, and then matches the most compatible tasks and resources 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 tasks done per resource. In this paper, we introduce a hierarchical fuzzy logic based system that uses evolutionary systems to tune the fuzzy membership functions, which result in an improvement in the overall output of the system. The new fuzzy-genetic based system was able achieve better improvement in tasks done per resource than the hierarchical fuzzy logic based system that was tuned by experts.
Keywords :
fuzzy logic; fuzzy set theory; genetic algorithms; quality of service; resource allocation; strategic planning; telecommunication industry; coarse-grain resource deployment; evolutionary systems; fuzzy membership function tuning; fuzzy-genetic tactical resource planner; hierarchical fuzzy logic-based system; medium-term planning periods; quality of service; resource utilization; tactical resource planning; telecommunication service; workforce allocation; Adaptive systems; Conferences; Fuzzy logic; Resource management; Schedules; Telecommunications; evolutionary systems; fuzzy logic systems; hierarchical fuzzy logic systems; tactical resource planning and telecommunications;
Conference_Titel :
Evolving and Adaptive Intelligent Systems (EAIS), 2013 IEEE Conference on
Conference_Location :
Singapore
DOI :
10.1109/EAIS.2013.6604111