Re-ordering policies for inventory systems with recyclable items and stochastic demand – Outsourcing vs. in-house recycling

Investing in recoverable items is an increasing trend in a variety of manufacturing industries. Such industries seek to balance their supply chain costs while reducing solid waste (non-biodegradable). Our work develops mathematical models of inventory systems that rely on newly manufactured and recoverable items to satisfy market demand. Specifically, we consider continuous (r, Q) re-ordering policies for single-item inventory systems with stochastic demand and recycling. The first model assumes outsourcing the recovery of used items to a supplier, where returns (collected used items) arrive in random quantities with every order. The second model assumes performing the recovery process in-house; i.e., at the manufacturer's facility. The proposed mathematical framework considers an infinite time horizon where demand and the amount recovered are stochastic. This work focuses on developing environmentally responsible inventory policies/models that could help in greening supply chains. It also presents a numerical study to compare the proposed models and quantify the trade-off cost between the two; i.e., should the recovery process be in-house or outsourced.