چكيده به لاتين
Oil industry is one of the biggest and most effective industries in the world. Petroleum supply chains contain complex structures and are affected by competition and price uncertainties, thus supply chain network planning and design is a tool to improve the industry. As supply chains become more complex, they become more vulnerable to disruptions; therefore, during supply chain design, paying attention to the approach that enables it to perform well when dealing with disruptions and unexpected events, which is called supply chain resiliency, is necessary. Duo to the characteristics of this industry, resilient designing for petroleum supply chain is really important. Since in the literature, the concept of disruption and resiliency has been neglected, so in this study a bi-objective two stage stochastic programming model for integrating upstream and midstream section of the petroleum supply chain under operational and disruption risks is presented. The model consists of two objective functions including net present worth and resilience measurement. In this study, it is assumed that supply chain is faced with two disruptions: crude oil transportation mode leads to export terminals and inaccessibility of octane rating of gasoline. In order to overcome existing disruptions, strategies such as increasing the capacity of refineries and using bioethanol to mix with gasoline have been used in the model. To evaluate the performance of the proposed model, a case study has been considered. Augmented epsilon constraint method was used to solve this multi - objective model by Gams software. Also, to investigate the effect of each important parameter of the problem and to validate the proposed model, sensitivity analysis is performed on the important parameters and the results are investigated. The results show that the further development of downstream petroleum supply chain, as well as replacing bioethanol instead of other octane rating, increase resiliency and net present value.
