Network design in scarce data environment using moment-based distributionally robust optimization

Hideaki Nakao, Siqian Shen, Zhihao Chen

Abstract: Highlights•We consider a distributionally robust network design (DR-NDP) model and construct an ambiguity set using marginal moments of random demand.•The goal is to minimize the worst-case total cost over all possible distributions.•We reformulate DR-NDP as a mixed-integer linear program solved by a cutting-plane algorithm.•We compare the results of DR-NDP with the ones of stochastic programming and robust optimization approaches.•DR-NDP provides more conservative results than the former and less conservative results than the latter.