Strategic network design for reverse logistics.

Abstract

Reverse logistics (RL) is gaining importance both in terms of research and industrial applications due to the thrust by the government, environmentalists and consumers to conserve resources. The issue in RL is to take back the used products, so that the product or its parts are appropriately disposed, recycled, reused, or remanufactured.

Most of the researchers do not recognize the complexity in handling returns of modular products. Also, most of the models proposed in the literature are not suitable for multi-product configurations. Thus, a deterministic optimization model is proposed to design a network for recovery of products. The model considers supply of return products, demand for the remanufactured products, supply of reusable modules and materials in the secondary market and is suitable for multi-product configurations. The network also considers suppliers of new modules to be used during the final assembly of the product. However, in practice, the return of used products and the demand for remanufactured products is uncertain. Hence, the base model is modified to incorporate stochastic supply and demand scenarios.

The proposed networks are analyzed by using simulated data to show the applicability of the model in real life situations. Scenario analyses are performed on the model to depict real life situations. The proposed network can assist in strategic decision making in RL networks.