A neutrosophic MACONT-LOPCOW decision support model for emergency logistics center selection during humanitarian crises

Abstract

This paper examines disaster preparedness and response, focusing on challenges encountered during natural disasters such as earthquakes. Therefore, we aim to develop a new and powerful tool based on type-2 neutrosophic numbers (T2NNs) for the selection of emergency logistics centers (ELCs). In this context, mixed aggregation based on a comprehensive normalization technique (MACONT) and logarithmic percentage change-driven objective weighting (LOPCOW) are systematically integrated with expert-based subjective weighting under a type-2 neutrosophic environment to construct a coherent decision-making framework for the ELC selection problem. We extend the MACONT method, which handles multiple normalization techniques, to incorporate the benefits into the T2NN-based environment. We combine the objective weights obtained using the LOPCOW method with the subjective weights derived from the T2NNs' structural features to accurately and rationally determine the weights of the criteria affecting the selection of the ELC. The proposed model offers a systematic decision-making process that incorporates criteria weighting and alternative ranking steps, effectively managing ambiguity and inconsistency in expert judgments. Based on real field data and expert opinions from the Kahramanmaras & cedil; earthquake, the proposed approach was applied to 19 criteria across four main categories and five possible ELC alternatives. The findings show that the proposed T2NN-based integrated approach produces more consistent, decision-maker-oriented results than traditional methods. In this context, the study makes meaningful contributions to the disaster management literature and practice by providing a methodological reference for decision-making problems under uncertainty in emergency logistics.