In this study, we are interested in the reusable containers management (e.g gases bottles, pallets, maritime containers, etc.). In this context, we address a dynamic reusable containers planning problem in a close-loop supply chain to optimize reusable containers collect, exploitation, storage and redistribution under environmental constraint in the context of reverse logistic. We propose firstly a new mixed integer programming model that helps practitioners to determine the delivered, collected, stored quantities of reusable containers on each period of the planning horizon under a carbon emission constraint. Secondly we introduce a hybrid approach based on the genetic algorithms to solve the problem. The numerical results have shown that developed hybrid approach generates high-quality solutions in a moderate computational time.