نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار گروه مهندسی صنایع، دانشگاه پیام نور، تهران، ایران

2 کارشناس ارشد، گروه مهندسی صنایع، دانشگاه پیام نور، تهران، ایران

چکیده

در این تحقیق مدلی برای یک زنجیره تامین حلقه بسته پایدار با در نظرگرفتن ملاحظات اقتصادی، اجتماعی و زیست محیطی به همراه ریسک ناشی از عدم قطعیت در پارامترها ارائه میگردد که برای مدلسازی این مسئله از برنامه ریزی تصادفی استفاده شده و همچنین با استفاده از مقیاس ارزش در معرض ریسک شرطی به اندازه‌گیری ریسک‌ها پرداخته میشود. هدف این مدل ماکسیمم کردن سود طراحی شبکه، کاهش نرخ بیکاری و افزایش فرصت های شغلی ناشی از احداث مراکزو مینیمم کردن کربن تولید شده حاصل از حمل‌و نقل‌های درون شبکه، مراکز تولید، بازیافت، تعمیر، تولید مجدد می‌باشد. از دیگر اهداف این مسئله می‌توان به مینیمم کردن ریسک ناشی از عدم قطعیت در هزینه حمل‌ونقل و تقاضای مشتری نیز اشاره نمود. در پایان جهت نشان دادن کارایی مدل، مثالی تحت شرایط قطعیت و عدم قطعیت با معیار اندازه‌گیری ریسک حل نموده و جوابهای بهینه پارتو آنها با هم مقایسه میگردد. نتایج این تحقیق بیانگر این مطلب می‌باشد که با افزایش ریسک، سود ناشی از شبکه زنجیره تامین کاهش یافته و جهت مواجه شدن با ریسک می بایست هزینه بیشتری را متحمل گردید.

کلیدواژه‌ها

عنوان مقاله [English]

Multi-objective optimization model for risk assessment in the supply chain of a closed close loop under uncertainty conditions in parameters: Using a Constrained Risk Value Approach (CVaR)

نویسندگان [English]

  • Meisam Jafari Eskandari 1
  • Hani Emami-Solot 2

1 Assistant Professor, Department of Industrial Engineering, Payam Noor University, Tehran, Iran

2 Senior Expert, Department of Industrial Engineering, Payam Noor University, Tehran, Iran

چکیده [English]

In this research, a model for a sustainable closed-loop supply chain with economic, social and environmental considerations, along with the risk arising from uncertainty in parameters, is presented. Stochastic programming has been used for modeling this problem and also using the scale of value Exposure to conditional risk is measured by risk. The aim of this model is to maximize network design benefits, reduce unemployment and increase job opportunities resulting from the construction of facilities and minimize the production of carbon produced through intranets, production centers, recycling, repair, re-production. Other goals include minimizing the risk posed by uncertainty in transportation costs and customer demand. In the end, in order to demonstrate the efficiency of the model, an example is solved with certainty and uncertainty with the risk measurement criterion, and the pareto optimal solutions are compared. Results show that, with increasing risk, the profit from the supply chain network has decreased and should be costlier to face the risk.
Introduction
Today, the necessity and importance of corporate responsibility and the social impact of companies have led managers and planners to give special attention to these aspects in their organization's missions, visions, and strategies. Corporate social responsibility encompasses the influence of a company's activities on various social groups, including employee rights, workplace safety, favorable working conditions, and job creation, among others. Furthermore, the significance of environmental standards and organizations' efforts to reduce pollution and promote efficient waste management and recycling practices have become crucial for organizational success, considering legal requirements and customer expectations. In recent years, the integration of reverse logistics, social responsibility, and environmental objectives in supply chain management has gained increasing attention due to factors such as resource reduction, pollution mitigation, environmental pressures, customer demands, and transportation costs in a competitive market. This integration, known as the closed-loop supply chain network, aims to ensure sustainability. Additionally, risk management within the supply chain has become a vital concern for supply chain management, considering the uncertainties prevailing in the global economy and trends such as increased outsourcing and advancements in information technology. The growing interest in achieving sustainability as an effective strategy for addressing challenges in the global supply chain has led to extensive research in the field of sustainable closed-loop supply chain management. However, previous studies in this area have lacked a comprehensive measure for assessing risk. Therefore, it is essential to address this issue, which involves considering stability goals in a closed-loop supply chain alongside risk management in uncertain conditions. The necessity for such research is evident, given the complexity of global supply chains and the increased vulnerability and risk exposure faced by organizations.
Materials and Methods
Given the existing gaps in the literature and the presence of uncertainty in real-world data, a mathematical model was proposed to help decision-makers reduce risk by considering identified risks and utilizing a comprehensive and effective risk measurement scale. In the designed model and forward network, suppliers are responsible for procuring raw materials. The manufactured products are then delivered to the market's customers through distributor networks. In the reverse flow of products, returned items are categorized into two groups: separable and non-separable products, after collection and inspection. Products that can be disassembled are sent to separation centers where they are transformed into components. The components are further divided into recoverable and non-recoverable categories. Non-recoverable components are transferred to disposal centers for safe disposal, while recoverable components are sent to inspection, cleaning, and sorting centers. After inspection and cleaning, the products are classified into repairable, remanufacturable, and recyclable groups. In the remanufacturing process, reusable components, after inspection, cleaning, and sorting, are sent to factories based on the production center's capacity. They are then combined with other parts to create new products that reenter the distribution cycle. In the recycling process, separated recyclable components are transported to recycling centers for direct production of raw materials, based on the capacity of the recycling centers, after collection and inspection.
Discussion and Results
Model 1 represents the initial approach, where scenario analysis for future conditions is not utilized, and the average values of uncertain parameters are taken into account. On the other hand, Model 2 incorporates various scenarios of future conditions. It is a linear model that considers possible future conditions as well. Model 1 exhibits lower costs compared to Model 2. The predictability of this problem arises from the fact that the risk associated with future market conditions was largely disregarded in Model 1. However, in Model 2, the consideration of introduced triple conditions for possible future outcomes necessitates a higher cost. Nevertheless, this higher cost brings us closer to real-world approximation and facilitates better decision-making in supply chain management when confronted with risks.
Conclusion
In this article, we conducted a literature review on the topic of risk models in supply chains and identified existing gaps. We found that most of the work in this field has certain weaknesses. Firstly, the focus has primarily been on risks in conventional and single-objective supply chains, neglecting the consideration of new risks and uncertainties that may arise in sustainable supply chains. To address this, we proposed a model for risk management in sustainable closed-loop supply chains. Secondly, we noticed that most of the existing studies lack a suitable and effective scale for measuring risk, particularly in the design of sustainable closed-loop supply chains. Drawing from the financial literature, we introduced the CVaR scale to fill this gap. Lastly, we developed and analyzed a model based on research gaps, using a case study in the home appliance industry as an example. The examination of the model's results, along with comparisons to real-world outcomes and previous research, validates the credibility of the proposed model.

کلیدواژه‌ها [English]

  • Sustainable closed loop supply chain
  • Conditional Value Risk Value (CVAR)
  • Random Planning
  • Uncertainty
زارعیان جهرمی، حسین، فلاح نژاد، محمدصابر، صادقیه، احمد، احمدی یزدی، احمد، ) 6989
مدل بهینه سازی چند هدفه استوار در طراحی زنجیره تأمین حلقه بسته پایدار. نشریه
- . پژوهش های مهندسی صنایع، دوره 9، شماره 9، صفحه 666 89
سلطانی تهرانی، مهدی؛ حسن پور، حسینعلی و رمضانی، سعید، ) 6981 ( مدل بهینه سازی دو هدفه
هزینه و کربن دی اکسید در زنجیره تأمین یکپارچه )مستقیم و معکوس( در حالت چند
محصولی و چند دوره ای. دومین کنفرانس بین المللی و آنلاین اقتصاد سبز، بابلسر، شرکت
پژوهشی طرود شمال.
صفار، محمدمهدی، شکوری گنجوی، حامد ورزمی، جعفر، ) 6981 ( طراحی یک زنجیره تأم ین
حلقه بسته سبز با در نظر گرفتن ریسک های عملیاتی در شرایط عدم قطعیت و حل آن با
الگوریتم NSGA II . نشریه تخصصی مهندسی صنایع، دوره 18 ، شماره 6، بهار و تابستان
. 6981 ، از صفحه 99 تا 1
عزیزی، محمدرضا و جعفری، حمیدرضا، ) 6989 ( ارائه یک مدل ریاضی برای طراحی شبکه
زنجیره تأمین حلقه بسته پایدار با در نظر گرفتن معیارهای انتخاب تأم ین کننده در شرایط
عدم قطعیت، کنفرانس بین المللی مهندسی صنایع و مدیریت پایدار، اصفهان، دانشگاه آزاد
اسلامی واحد لنجان.
فخر زاد، محمدباقر و صمدی دارافشانی ، مریم، ) 6989 ( یک رویکرد بهینه ساز ی پایدار برای
طراحی شبکه زنجیره تأمین حلقه بسته چندمحصولی تحت عدم قطعیت تقاضا و بازگشت .
سومین همایش ملی سوخت، انرژی و محیط زیست، تهران، پژوهشگاه مواد و انرژی.
فروزش، نازنین؛ توکلی مقدم، رضا و موسوی، سید میثم، ) 6989 ( ارزیابی ریسک های زنجیره
تأمین پایدار برای مسئله انتخاب تأمین کننده با به کارگ یری روش جدید تحلیل حالات
خرابی در محیط فازی با ارزش بازه ای، دومین کنفرانس ب ین الملل ی مهندسی صنایع و
سیستم ها، به صورت الکترونیکی، گروه مهندسی صنایع دانشگاه فردوسی.
محمدی، سمانه و ذگردی، سید حسام الدین، ) 6989 ( طراحی شبکه زنجیره تأمین پایدار در صنایع
پایین دستی نفت .دومین کنفرانس بین المللی مهندسی صنایع و سیستم ها ، گروه مهندسی
صنایع دانشگاه فردوسی.
326 | نشریه علمی مطالعات مدیریت صنعتی| سال بیستم |شماره 66 | پاییز 0210
مصطفی زاده، مهسا و جعفری، عزیزالله، ) 6981 ( ارائه مدل ریاضی چند هدفه برای طراحی شبکه
زنجیره تأمین پایدار با در نظر گرفتن مدیریت موجود . ی چهاردهمین کنفرانس ب ین الملل ی
مهندسی حمل ونقل و ترافیک، تهران، ایران.
Azizi, Mohammadreza and Jafari, Hamidreza, (2016) Presenting a mathematical model for the design of a sustainable closed loop supply chain network considering supplier selection criteria under conditions of uncertainty, International Conference on Industrial Engineering and Sustainable Management, Isfahan, Islamic Azad University Lanjan unit. [In Persian]
Baptista, S., Barbosa-Póvoa, P., Escudero, L., IsabelGomes, M., Pizarro, C., (2019) On risk management of a two-stage stochastic mixed 0–1 model for the closed-loop supply chain design problem. uropean Journal of Operational Research, Vol.274, pp.91-107.
Dehghanian, F., Mansour, S. (2009). Designing sustainable recovery network of end-of-life products using genetic algorithm. Resources, conservation and recycling, Vol.53, pp.559-570.
El-Sayed, M.,Afia,N., and EI-Kharbotly, A., (2010) A stochastic model for forward reverse Logistics network design under risk. Computers & industrial Engineering, Vol.58, pp.423-431.
Fakhrzad, Mohammad Baqer and Samadi Darafshani, Maryam, (2012) A sustainable optimization approach for the design of multi-product closed loop supply chain network under demand and return uncertainty. Third National Conference on Fuel, Energy and Environment, Tehran, Materials and Energy Research Institute. [In Persian]
Furozesh, Nazanin; Tavakoli Moghadam, Reza and Mousavi, Seyed Maitham, (2016) Evaluation of sustainable supply chain risks for the problem of supplier selection by applying a new method of analysis of failure states in a fuzzy environment with interval value, the second international conference on industrial and systems engineering, in electronic form, Department of Industrial Engineering, Ferdowsi University. [In Persian]
Giannakis, M., Papadopoulos, T., (2016) Supply chain sustainability: A risk management approach, International Journal of Production EconomicsVol.171, pp.455-470.
Goh, M. Meng F., (2009) managing supply chain risk and vulnerability. Springer-Verlag London Edition.1, chapter 8.
Govindan, K., Fattahi, M., (2017) Investigating risk and robustness measures for supply chain network design under demand uncertainty: A case
مدل بهینه سازی چند هدفه جهت ارزیابی ریسک در...؛ جعفری اسکندری و امامی سلوط | 322
study of glass supply chain, International Journal of Production Economics, Vol.183, pp.680-699.
Hassanzadeh Amin, S., Baki, F., (2017) A facility location model for global closed-loop supply chain network design. Applied Mathematical Modelling, Vol.41, pp.316-330.
Huang, H. Y., Chou, Y.C., and Chang, S. (2009). A dynamic system model for proactive control of dynamic events in full-load states of manufacturing chains. International Journal of Production Research, Vol.47, pp.2485-2506.
Jabbarzadeh, A., Haughton, M., Khosrojerdi, A., (2018) Closed-loop supply chain network design under disruption risks: A robust approach with real world application. Computers & Industrial Engineering, Vol.116, pp.178-191.
Mohammadi, Samaneh and Zagerdi, Seyyed Hosamuddin, (2016) Designing a sustainable supply chain network in downstream oil industries. Second International Conference on Industrial and Systems Engineering, Department of Industrial Engineering, Ferdowsi University. [In Persian]
Mustafazadeh, Mehsa and Jafari, Azizullah, (2014) Presenting a multi-objective mathematical model for designing a sustainable supply chain network considering inventory management. 14th International Conference on Transportation and Traffic Engineering, Tehran, Iran. [In Persian]
Nguyen, T,V.,Zhou, L., Lin, Y., (2017) A multi-objective, multi-product and multi-transportation mode sustainable closed-loop supply chain network design. IEEE Conference Publications, pp.1-6.
Park, S., Lee, T.E.,Sung, C.S., (2010) A three-level supply chain network design model with risk pooling and lead times. Transportation Research Part E, Vol.46, pp.563-581.
Paydar, M.M., Babaveisi, V., Safaei, A.A., (2017) An engine oil closed-loop supply chain design considering collection risk. Computers & Chemical Engineering, Vol.104, pp.38-55.
Safar, Mohammad Mahdi, Shokuri Ganjovi, Hamed Varzmi, Jafar, (2014) Designing a green closed loop supply chain considering operational risks in conditions of uncertainty and solving it with NSGA II algorithm. Industrial Engineering Specialized Journal, Volume 49, Number 1, pp.6-55 [In Persian].
Shi, Jianmai, Liu, Zhong, Tang, Luohao, Xiong, Jian, (2017) Multi objective optimization for a.closed loop.network design problem using an improved genetic algorithm. Applied Mathematical Modelling, Vol.45, pp.14-30.
Soltani Tehrani, Mehdi; Hasanpour, Hossein Ali and Ramezani, Saeed,
322 | نشریه علمی مطالعات مدیریت صنعتی| سال بیستم |شماره 66 | پاییز 0210
(2014) Two-objective optimization model of cost and carbon dioxide in integrated supply chain (direct and reverse) in multi-product and multi-period mode. The second international and online conference on green economy, Babolsar, Trud Shamal Research Company. [In Persian]
Song, W.,Ming, X., Liu,H., (2017) Identifying critical risk factors of sustainable supply chain management: A rough strength-relation analysis method. Journal of Cleaner Production, Vol.143, pp.100-115.
Sónia R. Cardoso, Ana Paula Barbosa-Póvoa, Susana Relvas, (2016) Integrating financial risk measures into the design and planning of closed-loop supply chains. Computers & Chemical Engineering, Vol.85, pp.105-123.
Tuncel, G., Alpan, G., (2010) Risk assessment and management for supply chain networks: A case study. Computers in Industry, Vol.61, pp.250-259.
Tyrrell Rockafellar, R., Uryasev, S., (2000) Optimization of conditional value -at- risk. journal of risk, Vol.2(3(, pp.21-24.
Zareian Jahormi, Hossein, Fallah Nejad, Mohammad Saber, Sadeghieh, Ahmad, Ahmadi Yazdi, Ahmad, (2013) Robust multi-objective optimization model in sustainable closed loop supply chain design. Journal of industrial engineering research, volume 2, number 3, page 111-93. [In Persian]
Zeballos, L.J., Méndez, C.A., (2017) Managing Risk in the Design of Product and Closed-Loop Supply Chain Structure. Computer Aided Chemical Engineering, Vol.39, pp.443-474.
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 Review, Vol.89, pp.182-214.