On Solving the Fuzzy Assignment Problem with Restrictions using the Fuzzy DEMATEL approach

Abstract

The fuzzy assignment problem represents a significant optimization methodology employed for the distribution of finite resources to various tasks within uncertain contexts. In real-world decision-making scenarios, the assignment process frequently encounters a multitude of constraints and ambiguous data, thereby rendering traditional optimization techniques less effective. The proposed framework utilizes triangular fuzzy numbers to encapsulate uncertainty in decision-making parameters and assesses the inter-dependencies among restriction criteria via fuzzy DEMATEL analysis. By elucidating the causal relationships and the extent of influence among constraints, the model facilitates more informed assignment decisions in the face of imprecise conditions. The methodology empowers decision-makers to prioritize pivotal constraints and enhance allocation efficiency while taking into account the inter-dependencies among criteria. A numerical example is provided to illustrate the applicability and efficacy of the proposed approach. The results indicate that the integration of fuzzy DEMATEL with fuzzy assignment with restrictions modeling yields a systematic and dependable decision-support framework for addressing intricate assignment challenges in uncertain environments.