Meta-heuristics for reverse logistics: A literature review and perspectives

Since the beginning of the 90s, many countries in the world have begun to pay great concern to the environment and raw material resources. This interest has led to the emergence of a set of new concepts in industry, among them reverse logistics (RL). RL, which offers the possibility to give a second life to end-of-life (EOL) products, has attracted attention from both producers and scientific researchers. Meanwhile reverse flow integration in the supply chain has given rise to many optimization problems. Most of these problems are proving to be difficult to solve; by the theory of complexity and experience from computational experiments, they are classified as difficult and complex to solve through exact methods or simulations. Instead scientists used a strong and efficient class of methods called meta-heuristics to solve them. In this paper, we review the previously published papers on reverse logistics and classify them on the basis of the meta-heuristic approaches adopted and the problem context of the reverse supply chain. Further, we discuss the power and flexibility of these methods for solving a set of RL problems. Finally, we discuss some future opportunities and directions for practitioners and researchers.