… -based robust optimization approach is taken to finding the most influential nodes. The
proposed robust optimization … So, for the first time in this paper, a robust optimization approach is …

… based on robust optimization. This paper focuses on LSGDM, considering the social relationship
… , this is the first consensus of LSGDM in social network based on robust optimization. …

… social experience or knowledge structure of DMs. Such an effect may be even greater in
LSGDM under social network… Robust Optimization (RO) becomes an excellent tool for mitigating …

… appear to bring robust optimization and machine learning approaches into social network
area. In … uncertainties and related research works in robust optimization and machine learning. …

… Finally, we apply robust optimization to obtain the priority weights of … , the robust optimization
method only requires the lower and upper bounds of consumer preferences, and it is robust …

… several networks arising from social networks or some artificial … the network. Similarly, the
weights between vertices are always uncertain, and we also construct the robust optimization …

… role in numerous applications of social network analysis. … a simultaneous optimization
algorithm for robust correlation … synthetic and real-world social network data demonstrate the …

… The present study proposes a robust optimization model for sustainable pharmaceutical
distribution network design under uncertainty. The model is able to determine the main and …

… we use the social network … robust optimization model based on the existing robustness
research and discuss how to maximize the robustness of the regional logistics weighted networks …

… In this study, both stochastic robust optimization and robust optimization … robust optimization,
while other uncertainties were treated using scenario-based stochastic robust optimization. …