王颖慧，北京科技大学

In this talk, we consider a distributed interval optimization problem (DIOP) with uncertainties, whose global function is formed by local convex interval functions. In seeking Pareto solutions for distributed interval optimization problem, we propose a scalarization of the interval optimization problem (DSIOP). Further, we provide the relationship between solutions of DSIOP and Pareto solutions of DIOP. With this relationship, we propose a distributed Primal-dual algorithm to seek a Pareto solution of DIOP with linear convergence rates. We also given a numerical example to show the effectiveness of the proposed algorithm.