نوع مقاله : مقاله پژوهشی - کاربردی

نویسندگان

1 دانشجوی دکتری، گروه مدیریت صنعتی، دانشکده مدیریت و اقتصاد، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران.

2 دانشیار، گروه مدیریت صنعتی، دانشکده مدیریت، تهران غرب، استاد مدعو دانشگاه علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران.

10.22105/dmor.2021.270853.1310

چکیده

هدف: در زنجیره­های تامین پیچیده امروزی، در پایدار بودن علاوه بر اهمیت کاهش هزینه­ها، دو منظر اجتماعی و زیست­محیطی نیز اهمیت زیادی به دست آورده­اند. این تحقیق به دنبال ارایه مدل زنجیره تامین چندسطحی پایدار در بخش تولید محصولات نیروگاهی گروه کارخانجات صنعتی و تولیدی می­باشد.
روش‌شناسی پژوهش: برای مساله مورد نظر، یک مدل ریاضی ارایه شده است که اهداف آن عبارتند از: حداکثرسازی مسئولیت اجتماعی، کمینه­سازی انتشار آلاینده­های زیست­محیطی و کمینه­سازی هزینه­های زنجیره تامین. با توجه به اینکه برنامه­ریزی پایدار زنجیره تامین مساله‌ای Np-Hard است، از الگوریتم فراابتکاری نهنگ و ژنتیک برای ارایه و حل مدل استفاده کرده­ایم.
یافتهها: جهت حل مدل ارایه شده، مسائل نمونه آزمایشی در سه گروه اندازه کوچک، متوسط و بزرگ با توجه داده­های شرکت اتمسفر طراحی گردیده و نتایج دو الگوریتم بهینه­سازی نهنگ و الگوریتم ژنتیک با توجه به شاخص­های مقایسه­ای کیفیت، پراکندگی، یکنواختی و زمان حل با یکدیگر مقایسه شده­اند.




اصالت/ارزش افزوده علمی: نتایج نشان داد الگوریتم نهنگ دارای توانایی بالاتر، جهت دستیابی به جواب­های باکیفیت­تر و نزدیک بهینه از منظر شاخص کیفیت و اکتشاف و استخراج ناحیه شدنی جواب از منظر شاخص پراکندگی، نسبت به الگوریتم ژنتیک می­باشد. نتایج شاخص یکنواختی و زمان حل نیز نشان داد، الگوریتم ژنتیک دارای زمان حل کمتر می­باشد و فضای جواب را به­صورت یکنواخت­تر جستجو می­کند.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Mathematical model of sustainable multilevel supply chain with meta-heuristic algorithm approach (Case study: ATMOSPHERE GROUP : Industrial and Manufacturing Power Plant)

نویسندگان [English]

  • Farzaneh Rezaee 1
  • Nazanin pilevari 2

1 PhD Student, Department of Industrial Management, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran.

2 Associate Professor, Department of Industrial Management, Faculty of Management, Tehran West, Visiting Professor of Science and Research University, Islamic Azad University, Tehran, Iran

چکیده [English]

Purpose: In the current complicated supply chains, sustainability and two social and environmental perspectives have significantly caught researchers’ attention due to their significant role in cost reduction. The present study aims to propose a sustainable multi-tier supply chain model for power plant products for industrial and manufacturing factories.
Methodology: To this end, a mathematical model was proposed with three objectives: maximizing the social responsibility, minimizing the emission of environmental pollutants, and reducing the costs of the supply chain. The whale and genetic metaheuristic algorithms were employed to propose and solve the model since sustainable supply chain planning was considered an NH-hard problem.
Findings: In order to solve the proposed model, the experimental sample was designed in three groups including small, medium, and large in terms of the data of Atmosphere Company. The results of whale optimization and genetic algorithms were compared according to the comparative indices of quality, dispersion, uniformity, and solving time.




Originality/Value: According to the results, the whale algorithm was able to provide higher quality and near-optimal solutions than genetic algorithm; in addition, by comparison, it could efficiently explore and extract possible areas of the solution in terms of quality and dispersion indices. However, a shorter amount of time was required for genetic algorithm to uniformly find solutions.

کلیدواژه‌ها [English]

  • Supply Chain
  • Sustainability
  • Whale Optimization Algorithm
Abdi, A., & Hajiaghaei-Keshteli, M. (2019). Investigation of a possible multi-objective model for the problem of stable closed loop supply chain by considering vehicle routing using new and hybrid Meta-Heuristic algorithms. Journal of modeling in engineering, 17(59), 67-85. (In Persian). DOI: 10.22075/jme.2019.14151.1389
Aravendan, M., & Panneerselvam, R. (2014). An integrated multi-echelon model for a sustainable closed loop supply chain network design. Intelligent information management, 6(6), 257-279. DOI: 10.4236/iim.2014.66025
Benyoucef, L., Xie, X., & Tanonkou, G. (2013). Supply chain network design with unreliable suppliers: a Lagrangian relaxation-based approach. International journal of production research, 51(21), 6435-6454.
Bhattacharjee, S., & Cruz, J. (2015). Economic sustainability of closed loop supply chains: a holistic model for decision and policy analysis. Decision support systems, 77, 67-68. https://doi.org/10.1016/j.dss.2015.05.011
Das, K. (2018). Integrating lean systems in the design of a sustainable supply chain model. International journal of production economics198, 177-190.
Dehghani, E., Behfar, N., & Jabalameli, M. S‎. (2016). Optimizing location, routing and inventory decisions in an integrated supply chain network under uncertainty. Gournal of industrial and systems engineering, 9(4), 93-111.
Devika, K., Jafarian, A., & Nourbakhsh, V. (2014). Designing a sustainable closed-loop supply chain network based on triple bottom line approach: a comparison of metaheuristics hybridization techniques. European journal of operational research, 235(3), 594-615.
Fallah-Tafti, A., Sahreian, R., Tavakkoli-moghadam, R., & Moeinpour, M. (2015). An interactive possibilistic programming approach for a multi-objective closed-loop supply chain network under uncertainty. International journal of systems science, 45(3), 283-299.
Fang, X., Du, Y., & Qiu, Y. (2017). Reducing Carbon emissions in a closed-loop production routing problem with simultaneous pickups and deliveries under Carbon Cap-and-Trade. Economic and business aspects of sustainability, 9(12), 2198-2210. https://doi.org/10.3390/su9122198
Fathi, M. R., Nasrollahi, M., & Zamanian, A. (2020). Mathematical modeling of sustainable supply chain networks under. Industerial management journal Tehran University, 11(4), 621-652. (In Persian). DOI: 10.22059/IMJ.2019.280393.1007588
Ghahremani Nahr, J. (2020). Improvement the efficiency and efficiency of the closed loop supply chain: Whale optimization algorithm and novel priority-based encoding approach. Decisions and operational research, 4(4), 299-315. (In Persian). DOI: 10.22105/dmor.2020.206930.1132
Golini, R., Longoni, A., & Cagliano, R. (2014). Developing sustainability in global manufacturing networks: the role of site competence on sustainability performance. International journal of production economics, 147, 448-459. https://doi.org/10.1016/j.ijpe.2013.06.010
Govindan, K., Shaw, M., & Majumdarc, A. (2020). Social sustainability tensions in multi-tier supply chain: a systematic literature review towards conceptual framework development. Journal of cleaner production, 279, 123075. https://doi.org/10.1016/j.jclepro.2020.123075
Hanczar, P. (2012). A fuel distribution problem – application of new multi-item inventory routing formulation. Procedia - social and behavioral sciences, 54, 726-735. https://doi.org/10.1016/j.sbspro.2012.09.790
Ivanov, D., Dolgui, A., Sokolov, B., & Ivanov, M. (2017). Optimal control representation of the mathematical programming model for supply chain dynamic reconfiguration. IFAC-papers online, 50(1), 4994-4999. https://doi.org/10.1016/j.ifacol.2017.08.900
Jiménez, M., Arenas, M., Bilbao, A., & Rodrı´guez, M. V. (2007). Linear programming with fuzzy parameters: an interactive method resolution. European journal of operational research, 177(3), 1599-1609.
Kiani, S., & Samouei, P. (2020). Multi-objective dynamic recycling-routing-inventory for different pharmaceutical items with considering discount in a closed-loop supply chain. Decision and operational research, 3(5), 290-311. (In Persian). DOI: 10.22105/dmor.2020.237709.1170
Lin, Y., Jia, H., Yang, Y., Tian, G., Tao, F., & Ling, L. (2018). An improved artificial bee colony for facility location allocation problem of end-of-life vehicles recovery network. Journal of cleaner production, 205, 134-144. https://doi.org/10.1016/j.jclepro.2018.09.086
Mahmudi, A., Mojibian, F., & Nouri Sabet, A. (2019). A mathematical model for supplier selection in supply chain considering inventory control and pricing problems. Journal of decisions and operational research, 4(1), 89-99. (In Persian). DOI: 10.22105/DMOR.2019.89845
Manavalan, E., & Jayakrishna, K. (2019). A review of internet of things (IoT) embedded sustainable supply chain for industry 4.0 requirements. Computers & industrial engineering, 127, 925-953. https://doi.org/10.1016/j.cie.2018.11.030
Nie, D., Li, H., Qu, T., Liu, Y., & Li, C. (2020). Optimizing supply chain configuration with low carbon emission. Journal of cleaner production271, 122539. https://doi.org/10.1016/j.jclepro.2020.122539
Nurjan Nia, K. P., Carvalho, M., & Costa, L. (2017). Green supply chain design: a mathematical modeling approach based on a multi-objective optimization model. International journal of production economics, 183, 421-432. https://doi.org/10.1016/j.ijpe.2016.08.028
Pilevari, N., Toloei, A., & Sanaei, M. (2013). A model for evaluating cloud-computing users. African journal of business management, 7(16), 1405-1413. https://academicjournals.org/journal/AJBM/article-full-text-pdf/16EC44326635
Radfar, R., & Nezafati, N. (2014). Classification of internet banking customers using data mining algorithms. Journal of information technology management, 6(1), 71-90. (In Persian). DOI: 10.22059/JITM.2014.50051
Revert, C., Gómez-Melero, E., & Cegarra-Navarro, J. G. (2016). The influence of corporate social responsibility practices on organizational performance: evidence from Eco-Responsible Spanish firms. Journal of cleaner production, 112(4), 2870-2884. https://doi.org/10.1016/j.jclepro.2015.09.128
Saaverda, M., Cricardo, M., Olive, C. H. D., & Freires, F. G. Me. (2018). Sustainable and renewable energy supply chain: a system dynamics overview. Renewable and sustainable energy reviews, 82, 247-259. https://doi.org/10.1016/j.rser.2017.09.033
 Shahriari, M. R., Pilevari, N., & Gholami, Z. (2016). The effect of information systems on the supply chain sustainability using DEMATEL method. Advanced computational science with application, 1, 47-56. DOI: 10.5899/2016/cacsa-00053
Sohrabi, T., Etemad, M., & Fathi, M. R. (2018). Mathematical modeling of green closed loop supply chain network with consideration of supply risk. Advances in mathemathcal modeling, 7(2), 103-112. (In Persian). DOI: 10.22055/JAMM.2018.18354.1303
Vafaeenezhad, T., Tavakkoli-Moghaddam, R., & Cheikhrouhou, N. (2019). Multi-objective mathematical modeling for sustainable supply chain management in the paper industry. Computers & industrial engineering, 135, 1092-1102. https://doi.org/10.1016/j.cie.2019.05.027
Zhalechian, M., Tavakkoli-Moghaddam, R., Zahiri, B., & Mohammadi, M. (2016). Sustainable design of a closed-loop location-routing-inventory supply chain network under mixed uncertainty. Transportation research part E: logistics and transportation review89, 182-214. https://doi.org/10.1016/j.tre.2016.02.011
Zhen, L., Huang, L., & Wang, W. (2019). Green and sustainable closed-loop supply chain network design under uncertainty. Journal of cleaner production, 227, 1195-1209. https://doi.org/10.1016/j.jclepro.2019.04.098