Social network multiple-criteria decision-making approach for evaluating unmanned ground delivery vehicles under the Pythagorean fuzzy environment

With the rapid development of instant delivery, the shrinking labor population and prevailing contact-free economy, companies have launched unmanned ground delivery vehicles (UGDVs) to replace human distribution with machines. To meet the requirements for selecting UGDVs and achieve better applications in community delivery, a multi-criteria decision-making (MCDM) framework, combining the self-confidence aggregation approach and social trust network, is proposed in this study. Based on the internal characteristics of UGDVs, a multi-criteria comprehensive evaluation system for UGDVs is constructed. Then, a trust propagation and aggregation mechanism to yield expert weights based on a social trust network is suggested. Further, a self-confidence Pythagorean fuzzy aggregation operator is proposed to enhance the credibility of the decision results and compensate for the defects of existing methods. Finally, a practical case is considered to demonstrate the complete process of the MCDM model and to conduct a comparative analysis and sensitivity analysis of the model.

Automated summary

This study proposes a multi-criteria decision-making (MCDM) framework combining the self-confidence aggregation approach and social trust network for selecting unmanned ground delivery vehicles (UGDVs) to achieve better applications in community delivery. A multi-criteria comprehensive evaluation system is constructed based on the internal characteristics of UGDVs. A trust propagation and aggregation mechanism is suggested to yield expert weights based on a social trust network. Additionally, a self-confidence Pythagorean fuzzy aggregation operator is proposed to enhance the credibility of the decision results.