سامانه مدیریت نشریات علمی دانشگاه شهید بهشتی

احمدپور, نصیر, قسیمی, صلاح الدین, چالاکی, کامیار, سلطان‌پناه, هیرش. (1404). مدلسازی استوار مبتنی بر سناریو برای زنجیره تأمین سبز- تاب‌آور با در نظر گرفتن تأمین‌کننده پشتیبان و مکان‌یابی و تخصیص هاب (مطالعه موردی: صنعت خودرو). , 15(2), 120-157. doi: 10.48308/jimp.15.2.120
نصیر احمدپور; صلاح الدین قسیمی; کامیار چالاکی; هیرش سلطان‌پناه. "مدلسازی استوار مبتنی بر سناریو برای زنجیره تأمین سبز- تاب‌آور با در نظر گرفتن تأمین‌کننده پشتیبان و مکان‌یابی و تخصیص هاب (مطالعه موردی: صنعت خودرو)". , 15, 2, 1404, 120-157. doi: 10.48308/jimp.15.2.120
احمدپور, نصیر, قسیمی, صلاح الدین, چالاکی, کامیار, سلطان‌پناه, هیرش. (1404). 'مدلسازی استوار مبتنی بر سناریو برای زنجیره تأمین سبز- تاب‌آور با در نظر گرفتن تأمین‌کننده پشتیبان و مکان‌یابی و تخصیص هاب (مطالعه موردی: صنعت خودرو)', , 15(2), pp. 120-157. doi: 10.48308/jimp.15.2.120
احمدپور, نصیر, قسیمی, صلاح الدین, چالاکی, کامیار, سلطان‌پناه, هیرش. مدلسازی استوار مبتنی بر سناریو برای زنجیره تأمین سبز- تاب‌آور با در نظر گرفتن تأمین‌کننده پشتیبان و مکان‌یابی و تخصیص هاب (مطالعه موردی: صنعت خودرو). , 1404; 15(2): 120-157. doi: 10.48308/jimp.15.2.120

مدلسازی استوار مبتنی بر سناریو برای زنجیره تأمین سبز- تاب‌آور با در نظر گرفتن تأمین‌کننده پشتیبان و مکان‌یابی و تخصیص هاب (مطالعه موردی: صنعت خودرو)

چشم‌انداز مدیریت صنعتی
دوره 15، شماره 2 - شماره پیاپی 58، 1404، صفحه 120-157    اصل مقاله (1.51 M)
نوع مقاله: مقاله پژوهشی
شناسه دیجیتال (DOI): 10.48308/jimp.15.2.120
نویسندگان
نصیر احمدپور1؛ صلاح الدین قسیمی* 2؛ کامیار چالاکی2؛ هیرش سلطان‌پناه3
1دانشجوی دکتری، گروه مدیریت صنعتی، واحد سنندج، دانشگاه آزاد اسلامی، سنندج، ایران.
2استادیار، گروه مهندسی صنایع، واحد سنندج، دانشگاه آزاد اسلامی، سنندج، ایران.
3دانشیار، گروه مهندسی صنایع، واحد سنندج، دانشگاه آزاد اسلامی، سنندج، ایران.
چکیده
مقدمه و اهداف: اجرای الزامات زیست محیطی به همراه کاهش هزینه­های لجستیکی، انتخاب تأمین کنندگان پایدار و مدیریت مناسب اختلالات، از جمله مسائل حیاتی و چالش‌برانگیز در مدیریت بهینه زنجیره تأمین به شمار می‌روند. این موضوعات به ویژه در صنایع حساس و با ماهیت پیچیده مانند صنعت خودرو اهمیت دوچندانی پیدا می‌کنند، چرا که این صنایع برای حفظ تداوم حیات، رقابت در بازارهای جهانی و رشد پایدار، ملزم به برنامه‌ریزی‌های دقیق، منسجم و کاربردی در سراسر زنجیره تأمین خود هستند. هدف اصلی این مطالعه ارائه یک مدل بهینه‌سازی چندهدفه‌ و استوار، مبتنی بر سناریو است که قادر باشد شبکه‌ای سبز، تاب‌آور و انعطاف‌پذیر را با ویژگی‌های چند محصولی، چند دوره‌ای، چند مواد اولیه و چند سطحی طراحی کند و در عین حال، عدم‌قطعیت‌های موجود در عرضه و تقاضا را به طور مؤثری مدیریت نماید.
روش‌­ها: مسائل مکان‌یابی و تخصیص هاب و سبز بودن تأمین‌­کنندگان اصلی و پشتیبان در طراحی شبکه در نظر گرفته شدند. همچنین کاهش هزینه‌­ها، برآوردن معیارهای محیط زیست و افزایش تاب‌­آوری در اهداف و محدودیت‌­های شبکه گنجانده شده است. برای مقابله با عدم‌قطعیت‌های عرضه و تقاضا، از رویکرد بهینه‌سازی استوار مبتنی بر سناریو استفاده شد. به منظور حل مسئله چندهدفه 10 مسئله کوچک و متوسط از طریق روش محدودیت اپسیلون تقویت­‌شده و 10 مسأله بزرگ توسط الگوریتم‌­های NSGAII و MOPSO حل گردید و نتایج حاصله از دیدگاه‌های مختلف ارزیابی و تحلیل شدند. پارامترهای الگوریتم‌های فراابتکاری بر اساس روش تاگوچی تعیین شدند. همچنین الگوریتم‌های فراابتکاری مورد استفاده بر اساس 5 معیار خطا، زمان، Diversity ، Spacing و MID با یکدیگر مقایسه شدند.
یافته‌­ها: نتایج نشان می‌­دهد که NSGAII الگوریتمی است که با توجه به معیارهای ارزیابی بهترین نتیجه را به دست می‌آورد. نتایج محاسباتی نشان می‌دهد که پیکربندی شبکه پیشنهادی می‌تواند به تقاضای مشتریان خود به شیوه‌ای سبز و تاب­‌آور پاسخ دهد. یک مطالعه موردی در صنعت خودرو ارائه گردید تا مشخص شود چگونه مدل پیشنهادی می‌­تواند نیازهای واقعی را پاسخ دهد. محل استقرار هاب‌­ها، میزان تخصیص و مراکز توزیع مرتبط با آنها برای شرکت ایران خودرو در نظر گرفته شدند. در نهایت، تحلیل حساسیت بر اساس چندین پارامتر با اهمیت انجام شد و پیش­بینی نتایج تشریح گردید.
نتیجه­‌گیری: نتایج نشان داد که مدل پیشنهادی آلودگی انتشاریافته توسط اعضای زنجیره و هزینه‌­های ثابت و متغیر مرتبط با اعضا که شامل هزینه قرارداد با تأمین‌کنندگان اصلی و پشتیبان، هزینه تأسیس هاب، هزینه تولید محصول و هزینه‌­های انتقال بین اعضای زنجیره می‌باشد را به حداقل می‌رساند. همچنین به کارگیری تأمین‌کننده پشتیبان تا حد زیادی توانسته است تاب‌آوری زنجیره را در مقابله با اختلالات ارتقا دهد. شبکه طراحی‌شده تاب‌آوری شرکت ایران خودرو را در مقابل این اختلالات افزایش داده است و می‌تواند مدیران ارشد شرکت را به منظور ارتقای عملکرد زنجیره صنعت خودرو کمک نماید. بر اساس یافته­‌های ما، اهمیت ظرفیت تأمین­‌کنندگان و هاب‌­ها بسیار برجسته است و اختلال در آنها سبب تغییر در راهبردهای شبکه می­شود. مدل پیشنهادی ما می­تواند شرکت ایران خودرو را در جهت دستیابی به برخی اهداف از قبیل عرضه به موقع محصولات منطبق با نیاز مشتری، استفاده بهینه از منابع، کاهش هزینه­ها و افزایش تاب‌آوری کمک نماید.
کلیدواژه‌ها
زنجیره تأمین سبز؛ زنجیره تأمین تاب‌­آور؛ تأمین­‌کننده پشتیبان؛ مکان‌­یابی و تخصیص هاب؛ بهینه­‌سازی چندهدفه؛ بهینه‌­سازی استوار مبتنی بر سناریو
عنوان مقاله [English]
Robust scenario-based modeling for green-resilient supply chain considering supporting supplier and hub location and allocation (case study: automotive industry)
نویسندگان [English]
Nasir Ahmadpoor1؛ Salahuddin Ghasimi2؛ Kamyar Chalaki2؛ Heirsh Soltanpanah3
1Ph.D. Student, Department of Industrial Management, Sa.C., Islamic Azad University, Sanandaj, Iran.
2Assistant Professor, Department of Industrial Engineering, Sa.C., Islamic Azad University, Sanandaj, Iran.
3Associate Professor, Department of Industrial Engineering, Sa.C., Islamic Azad University, Sanandaj, Iran.
چکیده [English]
Introduction and Purpose: Implementing environmental requirements along with reducing logistics costs, selecting sustainable suppliers, and appropriately managing disruptions are among the critical and challenging issues in optimal supply chain management. These issues are especially important in sensitive and complex industries such as the automotive industry, because these industries require precise, coherent, and practical planning throughout their supply chains to maintain their survival, compete in global markets, and grow sustainably. The main objective of this study is to present a multi-objective, robust, scenario-based optimization model that is capable of designing a green, resilient, and flexible network with multi-product, multi-cycle, multi-material, and multi-level characteristics, while effectively managing uncertainties in supply and demand.
Methods: The issues of location and allocation of hubs and the greenness of the primary and backup suppliers were considered in the network design. Efforts have also been made to reduce costs, meet environmental standards, and increase resilience in network objectives and limitations. The scenario-based robust optimization approach was used in the mathematical model to deal with supply and demand uncertainties. In order to solve the multi-objective problem, 10 small and medium problems were solved by the augmented -constraint method and 10 large problems were solved by the NSGAII and MOPSO algorithms, and the results were evaluated and analyzed from different perspectives. The parameters of the metaheuristic algorithms were determined based on the Taguchi method. Also, the metaheuristic algorithms used were compared with each other based on 5 criteria: error, time, diversity, spacing, and MID.  
Results and discussion: The findings show that the NSGAII algorithm achieves the best results according to the evaluation criteria. The computational results reveal that the proposed network configuration could respond to customer demand green and resiliently. A case study in the automotive industry was presented to determine how the proposed model can meet actual requirements. The location of the hubs, the allocation amount, and their associated distribution centers were considered for Iran Khodro Company. Finally, sensitivity analysis was performed based on several important parameters, and the prediction of the results was described.
Conclusions: The results showed that the proposed model minimizes the pollution emitted by the chain members and the fixed and variable costs associated with the members, which include the cost of contracting with the main and supporting suppliers, the cost of establishing the hub, the cost of product production, and the costs of transferring between the chain members. Also, the use of the supporting supplier has been able to greatly improve the resilience of the chain in dealing with disruptions. The designed network has increased the resilience of Iran Khodro Company against these disruptions and can help the company's senior managers to improve the performance of the automotive industry chain. Based on our findings, the capacity of suppliers and hubs is very important, and their disruption will cause changes in network strategies. Our proposed model can help Iran Khodro company achieve some goals such as timely supply of products according to customer needs, optimal use of resources, reducing costs, and increasing flexibility.
کلیدواژه‌ها [English]
Green Supply Chain, Resilient Supply Chain, Backup Supplier, Hub Location and Allocation, Multi-Objective Optimization, Scenario-Based Robustness
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