Disruption risks may halt or adversely affect supply chain operations and can lead to deviations in its objectives. One of the most important objectives of the supply chain which can be adversely affected by disruptions, is environmental objective. Therefore, considering supply chain resilience and environmental aspects simultaneously is of great importance. In this paper, the problem of designing a green and resilient mixed open and closed-loop supply chain network under operational and disruption risks has been studied. A bi-objective mixed integer linear programming model is proposed to formulate the problem. Some resilience strategies are applied to deal with disruption risks and enhance supply chain resilience. In order to overcome the complexity of the problem and solve the problems with medium and large sizes, a new meta-heuristic algorithm called multi-objective hybrid Ant-colony optimization and teaching and learning based optimization (ACO-TLBO) has been proposed and compared with two hybrid metaheuristics and the augmented ε-constraint method through various test problems. The outcomes showed that the ACO-TLBO algorithm is very efficient in obtaining high-quality Pareto solutions and is the best method among the proposed methods. Also, in order to show the applicability of the problem and validate the model and solution methods, a real case study in the tire industry has been presented and analyzed. The results of analyses demonstrate the high effectiveness of resilience strategies and the necessity of joint consideration of resilience and greenness in the supply chain design.