A type-2 fuzzy logic system for engineers estimation in the workforce allocation domain
Emmanuel Ferreyra, Hani Hagras, Ahmed Mohamed, Gilbert Owusu · 2017
Supplier companies aim to pursue an efficient resource allocation to different jobs over specific times and other constraints. Dynamic and unstructured environments and real-world situations incorporate a large amount of uncertainties which are difficult to model. This paper proposes a type-2 Fuzzy Logic System (FLS) for estimating the extra number of engineers required to allocate a certain number of jobs. The type-2 FLS was trained from the knowledge extracted dynamically from input data in order to estimate corresponding outputs for unseen data. The proposed methodology has been applied to real-world service provider industry in the workforce allocation domain. The system generated sensible results which outperformed the type-1 fuzzy logic based counterpart over unseen data.