Advanced Environmental Sciences

Advanced Environmental Sciences

Optimization of energy consumption and reduction of environmental emissions in cake production using data envelopment analysis and genetic algorithm

Document Type : Original Article

Authors
Asadollah Akram
Majid Khanali
Mahdieh Mohammadnia Galeshklamei
Homa Hosseinzadeh-Bandbafha
Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran
10.29252/envs.17.2.103
Abstract
Introduction:
Sustainable development necessitates the supply of energy resources in a sustainable manner, with a reasonable cost and with minimum negative social and environmental impacts. Thus the optimization of energy consumption, and as a result, the reduction of environmental emissions is of particular importance. The purpose of this study was to assess the amounts of consumed energy and pollutant emissions, optimization of energy consumption, and reduction in environmental emissions in the cake production industry in Guilan Province using data envelopment analysis (DEA) and genetic algorithm (GA).
Material and methods:
The efficient and inefficient units considering energy consumption were identified using DEA models. The optimal energy consumption pattern based on efficient units was presented for other cake production units, and the environmental assessment was performed based on the optimal pattern. Finally, using the multi-objective genetic algorithm (MOGA) and considering two objective functions aiming at increasing the yield and reducing the global warming (GW) index, the optimal energy consumption pattern in cake production units was presented.
Results and discussion:
The results of this study showed that 260532.25 MJ of energy was consumed for a daily production of 4157.14 kg of cake. The highest share of energy consumption was allocated to natural gas with 128582.1 MJ. Also, GW index was calculated 13099.49 kg CO2 eq. per ton of produced cake.According to DEA results, from a total of 21 cake production units, 17 units were recognized efficient based on variable returns to scale model. Based on DEA results, the total energy consumption for optimum consumption of inputs, the energy saving percentage, and the reduction of GW index were determined 254929.28 MJ day-1, 2.15%, and 550.18 kg CO2 eq. per ton of produced cake, respectively. Also, the energy use pattern proposed by the MOGA resulted in 36.3% reduction of energy consumption, in which the highest percentage of energy savings was associated with human labor. Based on the optimization results of MOGA, GW index for production of one ton of cake was calculated 10038.44 kg CO2 eq.
Conclusion:
MOGA optimization method in comparison to DEA, resulted in more reduction of energy consumption, GW index, production costs, and environmental burdens as well as higher income. Thus, the use of MOGA will pave the way for achieving sustainable development in cake production industry and staying in competition with other food industries.
Keywords
Genetic algorithm
Energy
Data Envelopment Analysis
Cake
Global warming
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Advanced Environmental Sciences
Volume 17, Issue 2
Summer 2019
Pages 103-124