Abstract
The current study integrates two strategic decisions, network configuration and selecting suppliers, for the green closed-loop supply chain under uncertainty. The demand and the rate of return are uncertain parameters. A robust multi-objective mixed-integer linear programming model is projected for the problem. The multi-period and multi-product model seeks to configure the network along with selecting suppliers and determining the type of technology used by manufacturers and recovery centres. The objectives include minimising the cost, minimising CO2 emission and maximising the weight of the suppliers. A two-stage model is utilised to solve the problem. The performance of the two-stage robust model is investigated in several numerical examples. The results revealed that the robust model compared to the deterministic model has better quality and is more reliable. Moreover, with a small additional cost, imposed by the robust model to face uncertainty, the robust model decreases the CO2 emission and has no infeasibilities.
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