طراحی مدل آماد معکوس چند دوره‌ای با مسیرهای متفاوت بازیابی محصول در شرایط عدم قطعیت

نوع مقاله : مقاله پژوهشی

نویسندگان

1 کارشناسی ارشد مدیریت صنعتی، موسسه آموزش عالی راهبرد شمال، رشت، ایران

2 استاد گروه مدیریت صنعتی، دانشکده مدیریت و اقتصاد، دانشگاه تربیت مدرس، تهران، ایران

3 استادیار، دانشگاه گیلان، رشت، ایران

چکیده

آماد معکوس از عمده‌ترین فعالیت‌های مدیریت زنجیره تأمین است که تمام فعالیت‌های فیزیکی مرتبط با محصولات بازگشتی مانند (جمع آوری، احیا، بازیافت و انهدام) را در بر می‌گیرد. یک موضوع ضروری برای مدلسازی سیستم‌های آماد معکوس، در نظر گرفتن تعداد بیشتری از گزینه‌های بازیابی و توجه به کیفیت بازگشتی‌ها و همچنین وجود عدم قطعیت، هم در مقدار و هم در کیفیت محصولات بازگشتی است. در این تحقیق، یک مدل برنامه‌ریزی عدد صحیح مختلط فازی دو مرحله‌ای جهت طراحی یک شبکه آماد معکوس یکپارچه چند دوره‌ای و چند محصولی تحت شرایط عدم قطعیت ارائه شده است. هدف نهایی، کمینه سازی هزینه کل شبکه است. مدل مورد بحث از نوع مسائل NP-Hard است که در آن، زمان حل مسأله به صورت نمایی افزایش می‌یابد. بنابراین در این تحقیق، از الگوریتم فراابتکاری ژنتیک برای حل مدل استفاده شده است.

کلیدواژه‌ها

عنوان مقاله [English]

Design of multi-period Reverse logistic model with different product recovery routes under uncertainty

نویسندگان [English]

  • nasser tarin 1
  • adel azar 2
  • seyyed abbas ebrahimi 3
1 Master of Industrial Management, Rahbord Shomal Institute of Higher Education, Rasht, Iran
2 Professor, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran.
3 Assistant Professor,University of Guilan, Rasht, Iran
چکیده [English]

One of the main activities of supply chain management is reverse logistics. Reverse logistic encompass all physical activities associated with returned products such as collection, recovery, recycling and disposal. An essential issue of modeling the problem of designing reverse logistic systems is considering the greater number of options regarding the quality of returns and also uncertainty in both quantity and the quality of the returned product. In this study, a two phase fuzzy mixed integer programming is proposed. Because some of parameters are fuzzy, this model design under uncertainty condition. Moreover, the reverse logistics network was developed as a multi-period and multi-product model. The objective function of model is minimizing the total cost of the network. The model is a type of NP-Hard problems which time of solution increases exponentially. Therefore, in this study, we use the genetic metaheuristic algorithm to solve the model.

کلیدواژه‌ها [English]

  • reverse logistic
  • returned products quality
  • Uncertainty
  • mixed integer programming model
  • genetic algorithm

مراجع

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