A stochastic dual dynamic integer programming based approach for remanufacturing planning under uncertainty

We seek to optimize the production planning of a three-echelon remanufacturing system under uncertain input data. consider multi-stage stochastic integer programming approach and use scenario trees represent information structure. introduce new dynamic formulation that relies on partial nested decomposition tree. then propose approximate dual algorithm based this decomposition. Our numerical results show proposed solution is able provide near-optimal solutions for large-size instances with reasonable computational effort.