A scenario-based stochastic optimization model for designing a closed-loop supply chain network considering sale and leaseback transactions

Nowadays, many researchers focus on reverse logistics and closed-loop supply chain network design. The main reason is the ever-increasing importance of environmental issues, customer satisfaction and economic benefits. In this paper, a scenario-based optimization model is proposed to deal with the closed-loop supply chain network design problem considering sale and leaseback (SLB) transactions. SLB transactions increase the liquidity of total assets and provide monetary resources for other activities. The proposed model, which is formulated based on sales accounting standards, maximizes the supply chain’s benefit after tax. The proposed model is solved to optimality. Finally, a sensitivity analysis on the safety stock coefficient, the fair value of the leased asset, the interest rate implicit in the lease and lessee's incremental borrowing rate is performed to assess the impact of these parameters on the expected value of supply chain’s benefit after tax.