Closed loop supply chain network design under uncertain price-sensitive demand and return

Abstract

In this paper, a closed-loop supply chain network design problem is developed. In the proposed model, expected returned products is estimated as a function of return price and if the amount of returned products is less than the expected amount, decision makers have some choices such as more advertising, incentives (extra cost) for returning more products. Different quality levels are considered for returned products which impacts on the recyclable and remanufacturable fractions of returned products as well as recovery lead time and cost. The model aims to maximize the total profit while making several decisions regarding pricing, the network design, material flow, quantity of manufacturing/remanufacturing, recycling, and inventory in an integrated manner to avoid any sub-optimality. A hybrid genetic algorithm and simulated annealing is proposed to solve the model. Numerical examples and sensitivity analysis are conducted to evaluate the applicability of the proposed model and lead to appropriate managerial decision about profitability of spending extra cost for returning more used products from customers.