Abstract
Bio-fuel is one of the most important alternatives to fossil fuels due to energy shortages. The bio-fuel is derived from biomass that is obtained from agricultural products such as plant debris. In addition, the supply chain is affected by risks which are due to several reasons such as economic, natural phenomena, political and etc. The occurrence of such events can cause disruption in supply chain which can significantly increase the total supply chain costs and also prevent serve to customers. Reliability is involved the capability of a network to achieve an anticipated process such as ``communication". Analysis of network reliability has acknowledged significant consideration and is consequently broadly studied to forecast and avoid any network failure. In order to distribute bio-fuel to the customers, designing a reliable and sustainable bio-fuel supply chain is very importance. Thus a growth in bio-fuel production demonstrates the requirement for establishing an effective and reliable network of chain that not only accomplishes sound under regular circumstances nevertheless restricted risk under various unanticipated disruption situations. This paper presents mathematical model to design an efficient bio-fuel supply chain network at pre-disaster stage that considering failure in the connecting links between the facilities. In which the probability of failure of the links is forecasted by a spatial statistic approach and also due to the fact that disasters can cause disruptions in bio-refineries, leads to use the risk-pooling effect in order to reduce total costs. In order to solve the proposed mathematical model, two meta-heuristic algorithms containing genetic algorithm (GA) and bat algorithm (BA) are utilized. The results show that by increasing the reliability and improvement of connecting links between facilities and considering the risk-pooling effect on disrupted bio-refineries, the total costs of supply chain can be considerably reduced.
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