چكيده به لاتين
In today's world, some issues like increase in energy demand, environmental pollution caused by fossil fuels, global warming and greenhouse effect, Failure to adhere to sustainable development, being non-renewable fossil fuel sources has made mankind seek a solution for an alternative energy, . Based on the above-mentioned ' Biodisels' can be appropriate suggestion. It should be noted that due to concerns such as farm land allocation, food supply and food market equilibrium, non edible feedstock used to produce biodiesel have been used.
This proposal plans a design of a multi-period and multi-product biodiesel supply chain network in respect of decreasing the costs under uncertainty.Uncertainty is introduced as a hybrid fuzzy type 2 stage stochastic programming method. Supply and process parameters (transportation costs and variable costs) and demand in stochastic and uncertainties fixed cost parameters of the centers are considered as fuzzy type -2 and There are three reduction methods for a type-2 triangular fuzzy variable (T2TrFV) by adopting the critical value (CV). Three generalized expected values (optimistic, CV and pessimistic) are derived for T2TrFVs with some special cases. Is discussed. expected values CV In this paper. The recommended model is able to determin the optimal number, location, capacity of the facility, appropriate transport modes, appropriate technology in the refinery, material flow and production planning in different periods. Also, Data Envelopment Analysis (DEA) is used to monitor the potential locations of the centers and to consider some effective indicators on the design of the biodiesel supply chain.In conclusion, the SAA method is suggested for Uncertain model. The suggested model for a real sample in Iran will be studied and solved by GAMS in following, The acquired results demonstrate the efficiency and performance of the proposed model in designing biodiesel supply chain network.
Keywords: Optimization of biodiesel supply chain, Two-stage stochastic programming, Data Envelopment Analysis (DEA), Average sample approximation method (SAA), fuzzy type -2, uncertainty
