طراحي مدل عامل¬بنیان برای بهينه¬سازي تولید و کنترل موجودی و مسیریابی در زنجيره تامين محصولات فسادپذير
محورهای موضوعی : مدیریت صنعتی
مهدی سوهانیان
1
(دانشجوی دکتری مدیریت صنعتی (گرایش سیستم‌ها)، دانشکده مدیریت و اقتصاد، وتحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران)
رضا احتشام راثی
2
(استادیار، گروه مدیریت صنعتی، دانشکده مدیریت و اقتصاد، واحد قزوین، دانشگاه آزاد اسلامی، قزوین، ایران )
رضا رادفر
3
(گروه مدیریت صنعتی، دانشکده مدیریت و اقتصاد، دانشگاه ازاد اسلامی واحد علوم و تحقیقات تهران، تهران، ایران)
کلید واژه: زنجیره تامین, محصولات فسادپذیر, شبیه¬سازی گسسته پیشامد, مدلسازی عامل بنیان, بهینه¬سازی,
چکیده مقاله :
هدف پژوهش ارائه مدل ترکیبی عامل¬بنیان – گسسته پیشامد به منظور بررسی یکپارچه برنامه ریزی تولید، کنترل موجودی و تعداد و نوع ناوگان در زنجیره تامین محصولات فسادپذیر است. مدل ترکیبی عامل¬بنیان به منظور پیاده¬سازی نقش هر عامل و نحوه ارتباط آنها در زنجیره تامین مورد استفاده قرار گرفته است. رویکرد شبیه¬سازی گسسته پیشامد به منظور پیاده¬سازی پیچیدگی¬های سطح خرد خطوط تولیدی استفاده شده است. زنجیره تامین فسادپذیر در سناریوهای بهینه¬سازی سطوح تولید و کنترل موجودی و بهینه¬سازی تعداد و نوع وسایل نقلیه مورد نیاز مورد ارزیابی قرار خواهد گرفت. به منظور یافتن مقادیر بهینه / نزدیک بهینه سطوح تولید و کنترل موجودی و تعداد و نوع وسایل نقلیه، از رویکرد شبیه¬سازی – بهینه¬سازی و الگوریتم¬های فراابتکاری بهره گرفته شده است. برای این منظور از نرم افزار AnyLogic برای مدلسازی عامل ها استفاده شده است. در این پژوهش سه سناریو جداگانه برای بررسی در نظر گرفته شده است. بهينه¬سازي سطح حداقل و حداکثر جهت توليد محصولات، بهينه¬سازي تعداد وسايل نقليه و نوع آنها و افزایش ظرفیت تولید با احداث خطوط تولیدی جدید. نشان می‌دهد، بهينه¬سازي سطوح توليد و موجودي با هدف کمينه کردن هزينه¬هاي نگهداري محصول و هزينه انتظار عامل توزيع¬کننده، تابع هدف 3 درصد بهبود و ميانگين مدت زمان دريافت سفارش تا تحويل محصول نيز 5 درصد بهبود می‌یابد.
The purpose of this research is to present a combined agent-based and discrete event model to investigate integrated production planning, inventory control, and the number and types of vehicles in the supply chain for perishable products. The agent-based model is employed to assess the role of various factors and their interrelationships within the supply chain. To account for the micro-level complexities of production lines, a discrete event simulation approach is utilized.To determine optimal or near-optimal production levels, inventory control, and the number and types of vehicles, a simulation-optimization approach is adopted, utilizing meta-heuristic and modeling algorithms in AnyLogic software. The simulation focuses on the production and routing of eight ice cream products distributed across three cold storage facilities. A total of 42 vehicles from four different types are used for transporting the products. To validate the model, discrepancies between actual values and those predicted by the model are assessed based on four key metrics: the quantity of products produced over one year, the number of shipments dispatched to distributors, the number of cooling system failures of machinery, and the count of products that recycle due to spoiled conditions. As all discrepancies for these four metrics are less than five, the validity of the model is confirmed.The results indicate that the objective function improves by 3%, while the average time from order receipt to product delivery is reduced by 5%. In the first scenario, product production is modeled based on the minimum and maximum available quantities as well as the minimum and maximum simulation values. In the second scenario, the number of vehicles is initially set at 42 but is reduced to 37 based on the proposed adjustments. Furthermore, the establishment of a new warehouse in Isfahan is recommended. With this new facility, the time interval from order receipt to delivery to distributors is expected to decrease to 131.6 hours. Additionally, considering the increase in production, the suggested optimal number of vehicles required for efficient operation is 44.
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