prioritizing local biomass resources for biofuel production by a fuzzy hybrid decision making approach (the case of hormozgan province in iran)

In recent years, increasing in energy demand and the importance of using energy with minimum green- house gas emission (ghg) leads researchers to study about renewable energy resources such as biomasses. biomasses can be converted to biofuels by applying the appropriate technologies. in this study, a hybrid group fuzzy multi-criteria decision making (mcdm) approach based on step-wise weight assessment ratio analysis (swara), technique for order preference by similarity to ideal solution (topsis), additive ratio assessment (aras), weighted aggregated sum product assessment (waspas) and simple additive weighting (saw) in the fuzzy environment is applied to rank biomasses in the case of hormozgan province in iran, because of being a coastal area and the access to different types of first, second and third generation resources of biofuel. after ranking these resources by mentioned methods, two aggregated multi-criteria decision making (mcdm) methods (mean rank method and copeland method) are employed to prioritize these biomasses.  results of mean rank show that municipal solid wastes (msw), fish wastes and microalgae have the minimum average rank, respectively and the results of copeland method show that msw, fish wastes and microalgae have the maximum (wins-loses), respectively. so, these biomasses are the most suitable ones in biofuel production in this province.