A SBM-NDEA Model for Evaluating the Efficiency of Cross-Docking Systems under Uncertainty: A Fuzzy Reasoning-Neutrosophic Programming Approach

Document Type : Research Paper

Authors

Department of Industrial Engineering, QA.C., Islamic Azad University, Qazvin, Iran

Abstract

– While the evaluation of warehouses' efficiency through various methods has been increasingly prominent in recent times, this study stands out as the pioneering attempt to evaluate the efficiency of cross-docking systems. To this end, this study delves into a detailed analysis of a cross-docking system's structure, taking into account a wide array of factors that impact its operational performance, such as inbound and outbound doors, different modes of transportation, inspection processes, kitting activities, storage procedures, retrieval tasks, and staging operations. A comprehensive range of key performance indicators (KPIs) is recommended for every aspect related to digitization, automation, sustainability, resiliency, and lean principles. A new slack-based measure network data envelopment analysis (SBM-NDEA) model is developed to assess the efficiency of cross-docking systems with regard to undesirable factors. What is more, a novel hybrid uncertainty method is presented, which incorporates fuzzy reasoning techniques and Neutrosophic fuzzy programming to address uncertainties in the recommended KPIs and quantify qualitative assessments. Ultimately, a case study is analyzed to highlight the efficacy and validity of the developed model and uncertainty methodology. The findings reveal that the simultaneous and effective application of pre-distribution and post-distribution policies can boost the efficiency of the analyzed system by 33%. Furthermore, modifying the layout to remove unnecessary transportation activities can result in a 21% improvement in efficiency.

Keywords


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