Assessment of optimized pattern in milling factories of rice production based on energy, environmental and economic objectives

Abstract

The aims of this study comprise energy optimization, economic analysis and life cycle assessment in converting paddy to white rice by data envelopment analysis (DEA) and multi-objective genetic algorithm (MOGA). For these purposes, 60 milling factories in Guilan province in Iran are assessed. Results indicate that the amount of energy input and output are 68178.31 MJ TIP−1 and 11894.64 MJ TIP−1, respectively, in converting paddy to white rice, in which natural gas consumption has a very high contribution to the total energy inputs. Life cycle assessment results show that background system for natural gas in milling factories and combustion of natural gas inside factories are environmental hotspots. Based on optimization results in converting paddy to white rice (mainly with lower natural gas consumption), reductions in energy consumption are 6 and 24%, reductions of global warming potential are 8 and 9%, and increase net profits are 24 and 41% by using DEA and MGOA, respectively. It can be said that MGOA is an appropriate optimization method to find the best mix in converting paddy to white rice inputs in order to attain energy, environmental and economic efficiencies.