مدل‌سازی دوهدفه مسئله مکان‌یابی تخصیص در یک زنجیره تأمین سبز با در‌نظر‌گرفتن سیستم حمل‌و‌نقل و انتشار گاز CO2

نویسندگان

1 دانشجوی دکتری، دانشگاه الزهرا.

2 دانشیار، دانشگاه الزهرا.

چکیده

در این پژوهش به مطالعه مسئله مکان­یابی تسهیلات در زنجیره تأمین سه‌سطحی، شامل کارخانه­ها، انبارها و خرده ­فروشان پرداخته شده است. انواع کالاها از طریق حالت­ های مختلف حمل ­و­نقل بین سطوح زنجیره منتقل می ­شوند. امروزه یکی از چالش ­های بسیار مهم در سازمان­ ها، کنترل انتشار گازهای گلخانه­ ای در سراسر شبکه است؛ بااین‌حال با توجه به پیچیدگی­ های مشکلات زنجیره تأمین سبز، ارائه مدل قابل­ حل دارای اهمیت زیادی است. در این پژوهش، به‌منظور ساده­ سازی مدل ریاضی، تنها CO2 منتشرشده در شبکه زنجیره تأمین در نظر گرفته شده است. هر تسهیل، مطابق با تقاضای ارسال­ شده، مقدار مشخصی از آلودگی را ایجاد می ­کند و آلودگی وسایل نقلیه به مسافت پیموده شده بستگی دارد. اهداف مدل پیشنهادی، کمینه ­کردن هزینه کل شبکه و کمینه­ کردن میزان انتشار گاز  COاست. روش حل پیشنهادی برای حل مدل ارائه‌شده، روش برنامه ­ریزی آرمانی چندگزینه ­ای است. به‌منظور بررسی کارایی روش­ پیشنهادی، یافته ­ها با نتایج به ­دست ­آمده از روش محدودیت اپسیلون مقایسه شده و تحلیل حساسیت پارامترهای ضروری صورت گرفته است.

کلیدواژه‌ها


1. Amiri, A. (2006). Designing a distribution network in a supply chain system: Formulation and efficient solution procedure. European Journal of Operational Research, 171(2), 567-576.

2. Arabzad, S. M., Ghorbani, M., & Ranjbar, M. J. (2017). Fuzzy Goal Programming for Linear Facility Location-Allocation in a Supply Chain; the Case of Steel Industry. International Journal of Research in Industrial Engineering, 6(2), 90-105.

3. Bal, A., & Satoglu, S. I. (2018). A Goal Programming Model for Sustainable Reverse Logistics Operations Planning and an Application. Journal of Cleaner Production.

4. Bayani Majd, A., Noori, S., Yaghoubi, S., Mohammadi, A. (2017). Green supply chain mathematical modeling for construction projects considering project scheduling. Journal of Industrial Management Perspective, 24, 123-156 (In Persian).

5. Chang, C. T. (2008). Revised multi-choice goal programming. Applied Mathematical Modelling, 32(12), 2587-2595.

6. Chang, C. T. (2011). Multi-choice goal programming with utility functions. European Journal of Operational Research, 215(2), 439-445.

7. Chibeles-Martins, N., Pinto-Varela, T., Barbosa-Póvoa, A. P., & Novais, A. Q. (2016). A multi-objective meta-heuristic approach for the design and planning of green supply chains-MBSA. Expert Systems with Applications, 47, 71-84.

8. Farahani, R. Z., Asgari, N., Heidari, N., Hosseininia, M., & Goh, M. (2012). Covering problems in facility location: A review. Computers & Industrial Engineering, 62(1), 368-407.

9. Hakimi, S. L. (1964). Optimum locations of switching centers and the absolute centers and medians of a graph. Operations research, 12(3), 450-459.

10. Hugo, A., & Pistikopoulos, E. N. (2005). Environmentally conscious long-range planning and design of supply chain networks. Journal of Cleaner Production, 13(15), 1471-1491.

11. Khishtandar, S., Zandieh, M., Dorri, B., Ranai Saadat, S.A. (2016). Green supply chain mathematical modeling for construction projects considering project scheduling. Journal of Industrial Management Perspective, 23, 29-54 (In Persian).

12. Kratica, J., Dugošija, D., & Savić, A. (2014). A new mixed integer linear programming model for the multi-level uncapacitated facility location problem. Applied Mathematical Modelling, 38(7), 2118-2129.

13. Mavrotas, G. (2009). Effective implementation of the ε-constraint method in multi-objective mathematical programming problems. Applied mathematics and computation, 213(2), 455-465.

14. Melkote, S., & Daskin, M. S. (2001). Capacitated facility location/network design problems. European journal of operational research, 129(3), 481-495.

15. Melo, M. T., Nickel, S., & Saldanha-Da-Gama, F. (2009). Facility location and supply chain management–A review. European journal of operational research, 196(2), 401-412.

16. Neto, J. Q. F., Walther, G., Bloemhof, J., Van Nunen, J. A. E. E., & Spengler, T. (2009). A methodology for assessing eco-efficiency in logistics networks. European Journal of Operational Research, 193(3), 670-682.

17. Oliver, R. K., & Webber, M. D. (1982). Supply-chain management: logistics catches up with strategy. In: Christopher, M.G. (Ed.), Logistics, The Strategic Issue. Chapman & Hall, London.

18. Pishvaee, M. S., & Razmi, J. (2012). Environmental supply chain network design using multi-objective fuzzy mathematical programming. Applied Mathematical Modelling, 36(8), 3433-3446.

19. Pishvaee, M. S., Razmi, J., & Torabi, S. A. (2012). Robust possibilistic programming for socially responsible supply chain network design: A new approach. Fuzzy sets and systems, 206, 1-20.

20. Raad, A., Sadeghi, A., Ghasemi, B. (2016). Two-echelon mathematical modeling with different manufacturers and multiple transportation modes in the supply chain. Journal of Industrial Management Perspective, 23, 77-100 (In Persian).

21. Rad, R. S., & Nahavandi, N. (2018). A novel multi-objective optimization model for integrated problem of green closed loop supply chain network design and quantity discount. Journal of Cleaner Production.

22. Rahmati, S. H. A., Hajipour, V., & Niaki, S. T. A. (2013). A soft-computing Pareto-based meta-heuristic algorithm for a multi-objective multi-server facility location problem. Applied Soft Computing, 13(4), 1728-1740.

23. Ratnayake, M. N., Kachitvichyanukul, V., & Luong, H. T. (2019). A Multi-Objective Model for Location-Allocation Problem with Environmental Considerations. In Environmental Sustainability in Asian Logistics and Supply Chains (pp. 205-217). Springer, Singapore.

24. Rezaee, A., Dehghanian, F., Fahimnia, B., & Beamon, B. (2017). Green supply chain network design with stochastic demand and carbon price. Annals of Operations Research, 250(2), 463-485.

25. Saffar, M., & Razmi, J. (2014). A new bi-objective mixed integer linear programming for designing a supply chain considering co2 emission. Uncertain Supply Chain Management, 2(4), 275-292.

26. Sarkar, B., & Majumder, A. (2013). A study on three different dimensional facility location problems. Economic Modelling, 30, 879-887.

27. Sarkar, B., Ganguly, B., Sarkar, M., & Pareek, S. (2016). Effect of variable transportation and carbon emission in a three-echelon supply chain model. Transportation Research Part E: Logistics and Transportation Review, 91, 112-128.

28. Shoul, A., Amiri, M., Olfat, L., Khalili Damghani, K. (2013). Multi-echelon and multi-product supply chain network design using combinational approach of multi-objective mathematical programming and data envelopment analysis. Journal of Industrial Management Perspective, 14, 117-137 (In Persian).

29. Talaei, M., Moghaddam, B. F., Pishvaee, M. S., Bozorgi-Amiri, A., & Gholamnejad, S. (2016). A robust fuzzy optimization model for carbon-efficient closed-loop supply chain network design problem: a numerical illustration in electronics industry. Journal of Cleaner Production, 113, 662-673.

30. Toro, E. M., Franco, J. F., Echeverri, M. G., & Guimarães, F. G. (2017). A multi-objective model for the green capacitated location-routing problem considering environmental impact. Computers & Industrial Engineering, 110, 114-125.

31. Weber, A., 1909. Uber Den Standort der Industrien, 1. Teil: Reine Theorie des Standortes.Tubingen, Mohr, Germany.

32. Wu, L. Y., Zhang, X. S., & Zhang, J. L. (2006). Capacitated facility location problem with general setup cost. Computers & Operations Research, 33(5), 1226-1241.