Abstract In this paper, we propose a stochastic variational inequality approach for a supply chain network, in which the cost functions (including both the production function and the transaction function) and the pricing cost function are contaminated by stochastic parameters. The proposed network structure of the supply chain is identified and the stochastic variational inequality model is derived for the supply chain network. A sampling approximation algortihm is proposed to solve the resulting stochastic variational inequality problem by combining Quasi-Monte Carlo sampling method and homogeneous interior point method. The global convergence of the algorithm is proved and a preliminary example is given to show the efficiency of the proposed method.