bi-objective stochastic programming model for green closed-loop supply chain network design in presence of sale and leaseback transactions

The need for effective use of assets has become more important in the design of supply chain networks in today’s competitive environment. sale and leaseback (slb) agreements are one of the appropriate tools to achieve this important goal. the proper use of these agreements increases the liquidity of assets, and provides financial resources required for other activities. however, the consideration of slb possibility in a closed-loop supply chain (clsc) that aims to minimize 〖co〗_2 emissions as well as maximizing profit has never studied before. therefore, this paper proposes a bi-objective two-stage stochastic program for designing a clsc network considering slb agreements. the objective functions are: to maximize profit after tax and to minimize 〖co〗_2 emissions of the supply chain. to assess the performance of the proposed model, 30 different-sized test problems are generated and solved by both lp-metric and max-min methods. finally, sensitivity analysis is performed to assess the impact of slb related parameters (the safety stock coefficient, the fair value of the leased asset, the interest rate implicit in the lease, and the lessee’s incremental borrowing rate) on the objectives. the results show significant superiority of the proposed model over which do not consider slb possibility. outcomes also indicates that lp-metric method provides better solutions for the problem. finally, some managerial insights are suggested.