A type-2 fuzzy logic system for engineers estimation in the workforce allocation domain

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.

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