Simultaneous optimization of closed- and open-loop supply chain networks with common components

In this paper, an integrated model that simultaneously optimizes the closed-loop supply chain (CLSC) and open-loop supply chain (OLSC) networks which use common components is described. A novel mixed integer programming (MIP) model is proposed to guarantee the optimal values of transportation amounts of assembled components and disassembled end-products in the CLSC and OLSC - which is also fed by CLSC - simultaneously while determining the location of facilities. Using a realistic network instance, computational results are presented for a number of scenarios to shed light on the effect of reverse rates, uncertainty in demand and capacity and size of the network. Results show that the simultaneous approach results in cost savings of 4.07% and 37.24% over the individual CLSC and OLSC solutions, respectively.