Optimization of energy consumption and environmental impacts of chickpea production using data envelopment analysis (DEA) and multi objective genetic algorithm (MOGA) approaches

摘要: Abstract Energy consumption in agricultural products and its environmental damages has increased recent centuries. Life cycle assessment (LCA) been introduced as a suitable tool for evaluation impacts related to product over life cycle. In this study, optimization of energy chickpea production was conducted using data envelopment analysis (DEA) multi objective genetic algorithm (MOGA) techniques. Data were collected from 110 enterprises face questionnaire the cropping season 2014–2015. The results revealed that, when applying MOGA, optimum requirement significantly lower compared application DEA technique; so total situation found be 31511.72 27570.61 MJ ha−1 by MOGA techniques, respectively; showing reduction 5.11% 17% relative current consumption. Optimization resulted acidification potential (ACP), eutrophication (EUP), global warming (GWP), human toxicity (HTP) terrestrial ecotoxicity (TEP) 29%, 23%, 10%, 6% 36%, respectively. capable reducing machinery, farmyard manure (FYM) diesel fuel nitrogen fertilizer (the mostly contributed inputs emissions) 59%, 28.5%, 24.58% 11.24%, Overall, technique showed superior performance approach optimizing system.