Abstract: Aiming at the deficiencies of traditional solution methods of independent-uncertain multi-objective programming problems, a novel solution approach under a new principle is proposed. Firstly, the basic framework of the approach is proposed and the concepts like Pareto efficient solution and expected-variance value principle are defined using the order relationship between different uncertain variables. Secondly, the original uncertain multi-objective problem is converted into an uncertain single objective programming problem by the linear weighted method or the ideal point method, and then it is transformed into a deterministic single objective programming problem under the expected-variance value principle. Thirdly, four lemmas and two theorems are proved to illustrate that the optimal solution of the deterministic single objective programming problem is an efficient solution of the original uncertain problem. Finally, two numerical examples are presented to illustrate the effectiveness of the proposed approach, and the genetic-particle swarm optimization algorithm and the binary wolf pack algorithm are adopted to solve them respectively.