Designing a Biodiesel Supply Chain Network by Considering Environmental FactorsUnder Uncertainty Conditions and solving it with the MOPSO algorithm

Subject Areas : Sustainable Development

gholamreza jandaghi ¹ , mohammad reza fathi ² , mohammad hasan maleki ³ , Meysam Molavi ⁴

1 - Professor., Department of Management and Accounting, College of Farabi, University of Tehran, Qom, Iran *(Correspondence Author)
2 - Associate Professor., Department of Management and Accounting, College of Farabi, University of Tehran, Qom, Iran
3 - Associate Professor, Department of Management, University of Qom, Qom, Iran.
4 - Phd of Industrial Management, Department of Management and Accounting, College of Farabi, University of Tehran, Qom, Iran.

Received: 2018-06-30 Accepted : 2018-08-13 Published : 2023-05-22

Keywords: Meta-Heuristic Algorithm, Fuzzy Multi-objective Programming, Supply Chain Network Design, Biodiesel,

Abstract :

Background and Objective: Increasing concerns about energy and greenhouse gas emissions from fossil fuel consumption have encouraged many researchers to be involved in developing sources of renewable energies. Biodiesel derived from biomass can play a crucial role in this context. The main objective of this paper is to present a mathematical programming model for the biomass supply chain. Material and Methodology: Researcher through library research and preparing a questionnaire to estimate parameters and data associated with the uncertainty of parameters and then through interviews, expert opinions about the limits and changes to the decision-making parameters have collected. Then a fuzzy multi-objective mixed integer programming model is presented that model to minimize costs, minimize environmental impact and minimize the time of delivery of product in Biodiesel Supply Chain. Findings: After running the model, increasing objective function is to minimize the total cost, minimize environmental impact and minimizing the time the product reaches the customer contact temperature limits for different values were obtained. Discussion and Conclusion: In this study, the proposed mathematical programming model is solved with the MOPSO algorithm. The results indicate the location and capacity of the facility, the amount of biodegradable and glycerin production, and the amount of extracted Jatropha oil and refined waste oils.

References:

1. Sathre, R. )2014(. Comparing the heat of combustion of fossil fuels to the heat accumulated by their lifecycle greenhouse gases, Fuel, 115, 674–677.


2. Bashiri, M and M. Sherafati. (2013). Advanced Bi-objective closed loop supply chain network design considering correlated criteria in fuzzy environment, Journal of Industrial Engineering Research in Production Systems, 1(1), 25-36. (In Persian)


3. Simchi- Levi, D., P. Kaminsky and E. Simchi- Levi. (2003). managing the Supply chain: The Definitive Guide for the Business professional, Mcgraw- hill.


4. Morrow, W.R., Griffin, W.M., Matthews, H.S. (2006). Modeling switchgrass derived cellulosic ethanol distribution in the United States, Environ. Sci. Technol, 40,2877–2886.


5. Ren, J., Manzardo, A., Toniolo, S., Scipioni, A., Tan, S., Dong, L., Gao, S. (2013). Design and modeling of sustainable bioethanol supply chain by minimizing the total ecological footprint in life cycle perspective, Bioresour Technol, 146, 771–774.


6. Sharma, B., Ingalls, R.G., Jones, C.L., Huhnke, R.L., Khanchi, A. (2013). Scenario optimization modeling approach for design and management of biomass-to-biorefinery supply chain system, Bioresour Technol, 150, 163–171.


7. Tong, K., Gleeson, M.J., Rong, G., You, F. (2014). Optimal design of advanced drop-in hydrocarbon biofuel supply chain integrating with existing petroleum refineries under uncertainty, Biomass Bioenergy, 60, 108–120.


8. Bairamzadeh, S., Pishvaee, M.S., Saidi-Mehrabad, M. (2015) Multi objective robust possibilistic programming approach to sustainable bioethanol supply chain design under multiple uncertainties, Ind. Eng. Chem. Res, 55, 237–256.


9. Babazadeh, R., Razmi, J., Pishvaee, M.S., Rabbani, M. )2016(. A sustainable second-generation biodiesel supply chain network design problem under risk, Omega, in press.


10. Tong, K., Gong, J., Yue, D., You, F. (2013). Stochastic programming approach to optimal design and operations of integrated hydrocarbon biofuel and petroleum supply chains, ACS Sustain. Chem. Engine, 2, 49–61.


11. Singh, A., Chu, Y., You, F. (2014). Biorefinery supply chain network design under competitive feedstock markets: an agent-Based simulation and optimization approach, Ind. Eng. Chem. Res, 53, 15111–15126.


12. Pishvaee, M.S. and Torabi S.A. (2010). A possibilistic programming approach for closed-loop supply chain network design under uncertainty, Fuzzy Sets and Systems, 161, 2668 –2683.


13. Tang, C.S. and Zhou, S. (2012). Research advances in environmentally and socially sustainable operations, European Journal of Operational Research, 223, 585–594.