چكيده به لاتين
Business environment, especially in the supply chain, is virtually fluctuating and is entangled with a lot of risks. Accordingly, a tailored mechanism should be adopted in order to deal with these operational and disruption risks in supply chains. Due to the importance of recycling and recovery of used and end of life products in many industries, there is always special attention to reverse supply chains and the related flows. In this regard, this thesis addresses a novel multi-objective integrated mixed integer linear programming model for designing a hybrid forward-reverse supply chain in order to avoid suboptimality caused by desiging each forward and reverse chain independently under operational and disruption risks. Used products after being inspected in collection centers can be transferred to disposal, repair or dismantling centers and sold in second-hand markets if they are repaired and recycled. In the proposed model, the objective functions include minimizing the total cost of the network, the environmental effects created by the supply chain, and ultimately maximizing the amount of social impacts, which are optimized simultaneously under disruption and operational risks. In this study a scenario-based approach has been used to deal with facility disruption conditions and in order to cope with disruption risks such as financial crises, loss of quality of raw materials, technology burnout, supply and storage problems and etc, some contingency and preventice resilience strategies have been applied, as well as to cope with the operational risks arising from the uncertain nature of the real world and the extreme fluctuation of parameters, an aghezzaf robust optimization approach is deployed. Eventually, a real automotive case study is conducted, via which the applicability and performance of the proposed model are endorsed. Due to the results obtained, concurrent implementation of disruption and operational risk management in the studied supply chain leads to overall improvement in sustainability objectives as well as reduction of costs resulting from the occurrence of risk in the chain. It should be noted that the greater the resiliency strategies used, especially the preventive strategies, the lower the costs of risk mitigation caused by the disruption.
