انتخاب تأمین کننده دریک زنجیره تأمین لارس چند محصولی وچنددوره ای بر پایه رویکردهای مدل سازی ریاضی، فرآیند تجزیه و تحلیل شبکه ای (ANP) و دیمتل (DEMATEL) (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
با توجه به فضای رقابتی بین تأمین کنندگان، مسأله انتخاب آن ها بر اساس معیارهای مهم برای تصمیم گیران به ویژه در زنجیره تأمین های لارس که ترکیبی از زنجیره تأمین پایدار و لارج است، بسیار حائز اهمیت می باشد. هدف این مقاله ارائه یک مدل ریاضی چندهدفه برای انتخاب تأمین کنندگان بر مبنای معیارهای مرتبط با مفاهیم زنجیره تأمین لارس است. ازنوآوری های مدل ارائه شده می توان به در نظر گرفتن همزمان چندهدف ، چنددوره ، چندمحصول و برنامه تولید اشاره کرد. کیفیت مدل ارائه شده بر روی یک مطالعه موردی در صنعت خودروسازی کشور مورد بررسی قرار گرفته است. در این مقاله ابتدا مهمترین معیارها از مرورادبیات استخراج و سپس از دید خبرگان صنعت خودروسازی کشور (مطالعه موردی در شرکت زامیاد) جمع بندی شد . به منظور بررسی روابط داخلی معیارها در هر دسته معیار از رویکرد دیمتل استفاده شده است. پس از مشخص شدن شبکه ارتباطات معیارها، میزان اهمیت هر معیار نسبت به معیار دیگر با استفاده از ماتریس مقایسات زوجی مشخص و به عنوان ورودی نرم افزار سوپردسیژن در نظر گرفته شد. در قسمت بعدی یک مدل ریاضی برای انتخاب بهینه تأمین کنندگان ارائه شده است. بر اساس نتایج بدست آمده، هزینه سفارش گذاری بیشترین تأثیر را بر تابع هدف داشته است. همچنین در نظرگیری مفهوم تقاضای پس افت، باعث بروز انعطاف در میزان تولید و در نتیجه کاهش هزینه های کلی شده است.Supplier selection in a multi-product, multi-period LARS supply chain based on mathematical modeling approaches, ANP and DEMATEL (Case Study: Zamiad Automotive Company)
Considering the competitive environment between suppliers, the issue of choosing them based on important criteria is very important for decision makers, especially in the LARS supply chain, which is a combination of sustainable and LARG supply chains. The aim of this paper is to present a multi-objective mathematical model for selecting suppliers based on criteria related to the LARS supply chain concepts. The innovations of the presented model include simultaneous consideration of multiple objectives, multiple periods, multiple products, and master production schedule. The quality of the presented model has been examined on a case study in the country's automotive industry. In this paper, at first, the most important criteria have been extracted from the literature, then finalized by experts in the country's automotive industry, and DEMATEL approach has been used to examine the internal relationships of the criteria in each category of criteria. Secondly, the network of criteria is determined, the importance of each criterion relative to the others was determined using a pairwise comparison matrix and considered as input to the Super Decision software. At last, a mathematical model for optimal supplier selection is presented. Based on the results obtained, the ordering cost had the greatest impact on the objective function. Also, considering the concept of backlog demand has led to flexibility in production volume and, as a result, reduced overall costs. Introduction LARG Supply Chain Management represents an integrated approach that combines lean, agile, resilient, and green paradigms in supplier relationship management. This holistic framework enables organizations to simultaneously leverage the advantages of each approach while compensating for their inherent limitations. For example, lean supply chain management focuses on minimizing inventory levels to reduce waste and cost; agile supply chain management emphasizes responsiveness and flexibility to meet dynamic market demands; resilient supply chain management enhances the ability to withstand and recover from disruptions; and green supply chain management aims to minimize environmental impacts and promote sustainability. According to Babaei et al. (2017), in an increasingly volatile and uncertain global environment, organizations are placing greater emphasis on supply chain resilience as a key capability for survival and competitiveness. Resilient supply chains are characterized by their capacity to absorb shocks and maintain operational continuity. Meanwhile, the concept of sustainable supply chain management—which addresses environmental, social, and economic concerns—has attracted growing interest among both academics and practitioners. More recently, researchers have begun to explore the LARS framework as a comprehensive model that overlaps with sustainability initiatives, particularly through its emphasis on green practices. However, despite their similarities, LARS and sustainability are distinct in scope and application. This study aims to identify a comprehensive set of criteria for supplier selection under the LARS framework, thereby supporting more informed and strategic decision-making in supply chain management. To this end, relevant criteria will be extracted through expert input from a leading firm in the Iranian automotive industry. In parallel, an extensive literature review will be conducted to incorporate practical and validated indicators associated with lean, agile, resilient, and sustainable supply chain practices. A Likert-scale-based questionnaire will be developed to assess suppliers against these criteria, and the resulting scores will serve as input for a multi-objective mathematical model. The remainder of this paper is structured as follows: Section 2 presents a review of the relevant literature. Section 3 introduces the proposed mathematical model. Section 4 details the case study and analyzes the results. Finally, Section 5 concludes the paper with key findings and managerial implications. Methods In this study, the most critical criteria were initially extracted through a thorough review of the existing literature and subsequently refined based on expert insights from the Iranian automotive industry, with a case study focused on Zamiad Company. To analyze the interrelationships among the criteria within each category, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was employed. Following the identification of the criteria interaction network, the relative importance of each criterion with respect to the others was determined using pairwise comparison matrices. These comparisons served as input data for the Super Decisions software, facilitating the application of the Analytic Network Process (ANP). In the next phase of the study, a mathematical model was developed to support the optimal selection of suppliers. Discussion and results In this research, the required data for all ten products were collected from the internal information systems of Zamiad Company. All collected data were evaluated in terms of consistency ratio, which was confirmed as being below 0.1, ensuring the reliability of the pairwise comparisons. After entering the data into Super Decisions software, the output—including the weights of each supplier for each product—were obtained. The results were reviewed and validated by experts at Zamiad Company. Although the proposed model is inherently nonlinear, it was linearized to reduce computational complexity. This adjustment significantly decreased the solution time, which is crucial when solving large-scale problems. The developed mathematical model aims to optimize the selection of suppliers for each product in each production period and to determine the allocated quantity to each supplier. The model incorporates various cost factors, including production, ordering, inventory holding, product shortage, and supplier switching costs. While the parameters of the model were intended to reflect actual company data, due to the confidentiality policies of Zamiad Company, some parameters were not accessible to the researchers. Therefore, these values were generated using normal distributions within predefined intervals based on expert judgment. The model was implemented over two six-month production periods, in alignment with Zamiad’s typical contractual arrangements with its suppliers. Based on the obtained results, ordering cost had the greatest impact on the objective function. Moreover, considering the concept of backlog demand has introduced flexibility in production volume, thereby reducing the overall costs. Conclusion This study aimed to identify key criteria affecting supplier selection and to determine their relative importance within the integrated LARS supply chain approach. Based on the obtained results, incorporating the production planning process reduces the diversity of suppliers across different periods. This can be attributed to production integration and the model’s preference for maintaining existing contracts over frequent changes. Given the current economic conditions in the production environment, it is essential to consider all relevant parameters in the supplier selection process simultaneously. The findings indicate that accounting for production planning within the LARS framework leads to more effective supplier selection. Among the evaluated parameters, production cost and product ordering cost had a greater impact on the overall performance of the proposed model compared to other factors. Therefore, managerial strategies should focus on controlling these key cost components. This research has contributed by identifying and evaluating these critical parameters.
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