When both purchase of new products and remanufacturing of returned products constitute options for a company, it faces a trade-off between the long purchase lead times and the high purchase costs versus the uncertainties generated by the unknown a priori quantity and quality of returns. In other words, although the remanufacturing of returns is generally a faster and less expensive alternative for a company, compared to the procurement of new products, both quality and quantity of returns are unfortunately highly stochastic. In such cases, companies have to select the ordering and remanufacturing policy so as to maximize their performance according to specific criteria, e.g., minimize the expected cost or maximize the expected profit. In this paper we investigate alternative policies for a system where both demand of new products and returns of used products are stochastic. The expected cost of each policy for a real application problem is computed and the best policy is proposed. A numerical investigation is also conducted in order to identify the best policy under various alternative scenarios.