A Fuzzy Goal-Programming Model for Optimization of Sustainable Supply Chain by Focusing on the Environmental and Economic Costs and Revenue: A Case Study

الموضوعات :

Mohammad Reza Zamanian ¹ , Ehsan Sadeh ² , Zeinolabedin Amini Sabegh ³ , Reza Ehtesham Rasi ⁴

1 - Department of Management, College of Human Science, Saveh Branch, Islamic Azad University, Saveh, Iran
2 - Department of Management, College of Human Science, Saveh Branch, Islamic Azad University, Saveh, Iran
3 - Department of Management, College of Human Science, Saveh Branch, Islamic Azad University, Saveh, Iran
4 - Department of Industrial Management, Qazvin Branch, Islamic Azad University, Qazvin, Iran

تاريخ الإرسال : 04 الإثنين , ربيع الأول, 1440 تاريخ التأكيد : 17 الأربعاء , جمادى الأولى, 1440 تاريخ الإصدار : 24 الجمعة , جمادى الثانية, 1440

الکلمات المفتاحية: Revenue, Fuzzy Goal Programming, Natural gas supply chain, Environmental cost, Economic cost,

ملخص المقالة :

Sustainable supply chain has become an integral part of the corporate strategy. In this paper, a real case study of the natural gas supply chain has been investigated. Using concepts related to natural gas industry and the relations among the compo-nents of gas and oil wells, refineries, storage tanks, dispatching, transmission and distribution network, a seven-level supply chain has been introduced and present-ed schematically. The aim of this paper is to optimize a case study using a fuzzy goal-programming multi-period model considering environmental and economic costs and revenue as fuzzy goals and maximize the total degree of satisfaction of goals as objective function. A small-sized problem was solved using GAMS 23.2.1 software and sensitivity analysis was conducted on its parameters. To the best of our knowledge, this is the first study that presents a fuzzy goal program-ming model for the optimization of sustainable natural gas supply chain by focus-ing on the environmental and economic costs and total revenue of gas products and the other main contribution of this research is focused to the developing of the mentioned model.

المصادر:

[1] Akoz, O., Petrovic, D., A fuzzy goal programming method with imprecise goal hierarchy, Eur. J. Oper. Res, 2007,181, P.1427–1433. Doi:10.1016/j.ejor.2005.11.049.

[2] Al-Sobhi, S.A., Elkamel, A., Simulation and optimization of natural gas processing and production network consisting of LNG, GTL, and methanol facilities, Journal of Natural Gas Science and Engineering, 2015, 23(2), P.500–508. Doi:10.1016/j.jngse.2015.02.023.

[3] Azadeh, A., Raoofi, Z., Zarrin, M., A multi-objective fuzzy linear programming model for optimization of natural gas supply chain through a greenhouse gas reduction, Journal of Natural Gas Science and Engineering, 2015, 26, P.702–710. Doi:10.1016/j.jngse.2015.05.039.

[4] Azadeh, A., Shabanpour, N., Soltanpour Gharibdousti, M., Nasirian, B., Optimization of supply chain based on macro ergonomics criteria: A case study in gas transmission unit, Journal of Loss Prevention in the Process Industries, 2016, (in press). Doi: 10.1016/j.jlp.2016.05.024.

[5] Chen, L. H., Tsai, F. C., Fuzzy goal programming with different importance and priorities, Eur. J. Oper. Res, 2001, 133, P.548–556. Doi:10.1016/S0377-2217(00)00201-0.

[6] Contesse, L., Ferrer, J.C., Maturana, S., A mixed-integer programming model for gas purchase and transportation, Ann. Operations Res, 2005,139(1), P.39–63. Doi: 10.1007/s10479-005-3443-0.

[7] Doaei, M., Davarpanah, S.H., Zamani Sabzi, M., ANN-DEA approach of corporate diversification and efficiency in bursa Malaysia, Advances in Mathematical Finance & Applications, 2017, 2(1), P.9-20. Doi:10.22034 /amfa.2017.529058.

[8] Dos Santos, S.P., Leal, J.E., Oliveira, F., The development of a natural gas transportation logistics management system, Energy Policy, 2011, 39(9), P.4774–4784. Doi:10.1016/j.enpol.2011.06.047.

[9] Dovi, M.S., Meshalkin, V.P., Mathematical Methods for the Multi-Criteria Optimization of Structure and Management of Energy Efficient Gas Supply Chains, Theoretical Foundations of Chemical Engineering, 2017, 51(6), P.1080–1091. Doi: 10.1134/S0040579517060033.

[10] Duffuaa, S.O., Al-Zayer, J.A., Al-Marhoun, M.A., Al-Saleh, M.A., A linear programming model to evaluate gas availability for vital industries in Saudi Arabia, J. Oper. Res. Soc, 1992, 43(11), P.1035–1045. Doi:10.1057/jors.1992.161.

[11] Esfandiar, M., Saremi, M., Jahangiri Nia, H., Assessment of the Efficiency of Banks Accepted in Tehran Stock Exchange Using the Data Envelopment Analysis Technique, Advances in Mathematical Finance & Applications, 2018,4(2), P.1-11. Doi: 10.22034/amfa.2018.540815.

[12] Fahimnia, B., Jabbarzadeh, A., Marrying supply chain sustainability and resilience: A match made in heaven, Transportation Research Part E, 2016, 91, P.306–324. Doi:10.1016/j.tre.2016.02.007.

[13] Ghaithan, A.M., Attia, A., Duffuaa, S.O., Multi-objective optimization model for a downstream oil and gas supply chain, Applied Mathematical Modelling, 2017, 52, P.689–708. Doi:10.1016/j.apm.2017.08.007

[14] Hamedi, M., Farahani, R.Z., Husseini, M.M., Esmaeilian, G.R., A distribution-planning model for natural gas supply chain: A case study, Energy Policy, 2009, 37(3), P.799–812. Doi:10.1016/j.enpol.2008.10.030.

[15] Iran Energy Balance, Energy Management Department, Institute for International Energy Studies (IIES), subsidiary of Ministry of Oil & Gas, 2017.

[16] Jamshidi, R., Ghomi, S.F., Karimi, B., Multi-objective green supply chain optimization with a new hybrid memetic algorithm using the Taguchi method, Sci. Iran, 2012, 19(6), P.1876–1886. Doi:10.1016/  j.scient.2012.07.002.

[17] Jayaraman, R., Liuzzi, D., Colapinto, C., Malik, T., A fuzzy goal programming model to analyze energy, environmental and sustainability goals of the United Arab Emirates, Ann Oper Res, 2015, 226.
Doi:10.1007/s10479-015-1825-5.

[18] Kabirian, A., Hemmati, M.R., A strategic planning model for natural gas transmission networks, Energy policy, 2007, 35 (11), P.5656–5670. Doi:10.1016/j.enpol.2007.05.022.

[19] Kalantari, N., Mohammadi Pour, R., Seidi, M., Shiri, A., Azizkhani, M., Fuzzy goal programming model to rolling performance based budgeting by productivity approach (Case Study: Gas Refineries in Iran), Advances in Mathematical Finance & Applications, 2018, 3(3), P.95 -107. Doi:10.22034/amfa.2018.544952.

[20] Liang, T.F., Integrating production-transportation planning decision with fuzzy multiple goals in supply chains, Int. J. Prod. Res, 2007, 46, P.1477–1494. Doi: 10.1080/00207540600597211.

[21] Mahdavi, I., Mahdavi-Amiri, N., Makui, A., Mohajeri, A., Tafazzoli, R., Optimal gas distribution network using minimum spanning tree, In: Proceedings of 2010 IEEE the 17th International Conference on Industrial Engineering and Engineering Management, 2010, 2. Doi: 10.1109/ICIEEM.2010.5646007.

[22] Mahlke, D., Martin, A., Moritz, S., A simulated annealing algorithm for transient optimization in gas networks, Math. Methods Operations Res, 2007, 66(1), P.99–115. Doi:10.1007/s00186-006-0142-9.

[23] Narasimhan, R., Goal programming in a fuzzy environment, Decis. Sci, 1980, 11, P.325–336. Doi:10.1111/ j.1540-5915.1980.tb01142.x.

[24] Nikbakht, M., Zulkifli, N., Ismail, N., Sulaiman, S., Sadrnia, A., Suleiman, M., Multi-echelon Supply chain design in natural Gas industry, World Applied Sciences Journal, 2012, 20(1), P.54–63. Doi:10.5829 /idosi. wasj.2012.20.01.862.

[25] Ozceylan, E., Paksoy, T., Fuzzy multi-objective linear programming approach for optimizing a closed-loop supply chain network, Int. J. Prod. Res, 2012, 51, P.2443–2461. Doi:10.1080/00207543.2012.740579.

[26] Pishvaee, M.S., Razmi, J., Environmental supply chain network design using multi-objective fuzzy mathematical programming, Appl. Math. Model, 2011, 36(8), P.3433–3446. Doi: 10.1016/j.apm.2011.10.007.

[27] Rajeev, A., Pati, R.K., Padhi, S.S., Govindan, K., Evolution of sustainability in supply chain management: A literature review, Journal of Cleaner Production, 2017, 162, P.299–314.Doi:10.1016/j.jclepro. 2017.05.026.

[28] Rostamzadeh, R., Keshavarz Ghorabaee, M., Govindan, K., Esmaeili, A., Bodaghi Khajeh Nobar, H., Evaluation of sustainable supply chain risk management using an integrated fuzzy TOPSIS- CRITIC approach, Journal of Cleaner Production, 2018, 175, P.651–669. Doi:10.1016/j.jclepro.2017.12.071.

[29] Santibanez-Gonzalez, E.D.R., Mateus, G.R., Luna, H.P., Solving a public sector sustainable supply chain problem: a genetic algorithm approach, In: Proc. Of Int. Conf. of Artificial Intelligence (ICAI), Las Vegas, USA, 2011, P.507–512. citeseerx.ist.psu.edu/viewdoc/summary? Doi:10.1.1.217.6885.

[30] Sapkota, K., Oni, A.O., Kumar, A., Techno-economic and life cycle assessments of the natural gas supply chain from production sites in Canada to north and southwest Europe, Journal of Natural Gas Science & Engineering, 2018, (in press). Doi: 10.1016/j.jngse.2018.01.048.

[31] Selim, H., Araz, C., Ozkarahan, I., Collaborative production–distribution planning in supply chain: a fuzzy goal programming approach, Transp. Res. Part E: Logist. Transp. Rev, 2008, 44, P.396–419.Doi:10.1016/ j.tre.2006.11.001.

[32] Selim, H., Ozkarahan, I., A supply chain distribution network design model: an interactive fuzzy goal programming-based solution approach, Int. J. Adv. Manuf. Technol, 2008, 36, P.401–418.Doi:10.1007/s00170-006-0842-6.

[33] Tabkhi, F., Pibouleau, L., Azzaro-Pantel, C., Domenech, S., Total cost minimization of a high-pressure natural gas network, J. Energy Resour. Technol, 2009, 131(4), 043002. Doi:10.1115/1.4000325.

[34] Tiwari, R.N., Dharmar, S., Rao, J.R., Fuzzy goal programming - an additive model, Fuzzy Sets Syst, 1987, 24, P.27–34. Doi:10.1016/0165-0114(87)90111-4.

[35] Torabi, S.A., Hassini, E., An interactive possibilistic programming approach for multiple objective supply chain master planning, Fuzzy Sets Syst, 2008, 159, P.193–214. Doi:10.1016/j.fss.2007.08.010.

[36] Vance, L., Heckl, I., Bertok, B., Cabezas, H., Friedler, F., Designing sustainable energy supply chains by the P-graph method for minimal cost, environmental burden, energy resources input, Journal of Cleaner Production, 2015, 94, P.144–154. Doi:10.1016/j.jclepro.2015.02.011.

[37] Wu, Y., Lai, K.K., Liu, Y., Deterministic global optimization approach to steady state distribution gas pipeline networks, Optim. Eng, 2007, 8(3), P.259–275Doi:10.1007/s11081-007-9018-y.