A multi-phase mathematical programming approach to strategic planning of an efficient reverse supply chain network

Strategic planning of a supply chain network is one of the most challenging aspects of reverse logistics. To effectively satisfy drivers such as profitability, environmental regulations and asset recovery, only the most economical used products must be reprocessed in only the recovery facilities that have the potential to efficiently reprocess them. Due to uncertainties in supply, quality and reprocessing times of used-products, the cost-benefit function in the literature that selects the most economical product to reprocess from a set of used-products is not appropriate for direct adoption. Moreover, due to the same uncertainties, any traditional forward supply chain approach to identify potential manufacturing facilities cannot be employed to identify potential recovery facilities. This paper proposes a three-phase mathematical programming approach, taking the above uncertainties into account, to completely design a reverse supply chain network. Application of the approach is detailed through an illustrative example in each phase.