A fuzzy-based decision support model for monitoring on-time delivery performance: A textile industry case study
This paper investigates uncertainties in complex supply chain situations and proposes a fuzzy-based decision support model for determining the chance of meeting on-time delivery in a complex supply chain environment. It integrates fuzzy logic principles and unitary structure-based supply chain model and enables addressing uncertainties associated with key inputs of on-time delivery performance for effective decision making process. The proposed pragmatic model deals with the fuzziness of the key inputs including, variations in demand forecasting, materials shortages and distribution lead time, and combines a fuzzy reasoning approach for monitoring on-time delivery of finished products. In systematically dealing with the uncertainties of complex supply chains, this model supports the minimizing of business losses that result from penalties and customer dissatisfaction, and the consequent reduced market share. Application of the proposed model is illustrated using a textile industry case study.
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