برنامه‌ریزی تصادفی دومرحله‌ای مبتنی بر روش تقریب میانگین نمونه و الگوریتم تجزیه بندرز شتاب‌یافته برای طراحی شبکه زنجیره تأمین حلقه بسته تحت عدم قطعیت

نوع مقاله: پژوهشی

نویسنده

دانشکده مهندسی صنایع و مدیریت دانشگاه شاهرود

چکیده

در این مقاله یک مدل ریاضی جامع برای طراحی شبکه زنجیره تأمین با در نظر گرفتن جریان‌های مستقیم و برگشتی به صورت توأم متعلق به چندین محصول در طی چند دوره زمانی ارائه‌شده است. عدم‌قطعیت پارامترهای تقاضا، نرخ‌های برگشت، احیا و امحا محصولات و هزینه‌های حمل‌ونقل، نگهداری و مدیریت جریان برگشتی با استفاده از برنامه‌ریزی تصادفی دو مرحله‌ای در نظر گرفته شده است. مدل ارائه‌شده با استفاده از یک روش حل کارا مبتنی بر تقریب میانگین نمونه و الگوریتم تجزیه بندرز شتاب‌یافته جدید حل شده است. الگوریتم تجزیه بندر ارائه‌شده با استفاده از روش ابتکاری اولویت‌دهی و اضافه‌نمودن یک محدودیت جدید به مسئله اصلی با هدف بهبود در سرعت همگرایی و ارائه برش‌های بهتر توسعه داده شده است. نتایج حل مدل ارائه‌شده برای مسائل نمونه متعلق به یک زنجیره تأمین تلفن همراه، حاکی از برتری جواب‌های حل برنامه‌ریزی تصادفی نسبت به حل قطعی و کارایی الگوریتم تجزیه بندرز شتاب‌یافته است. علاوه بر آن، جواب‌های برنامه‌ریزی احتمالی از استواری بیشتری نسبت به جواب‌های قطعی برخوردار هستند.

کلیدواژه‌ها


عنوان مقاله [English]

Two Stage Stochastic Programing Based on the Sample Average Approximation and Accelerated Benders Decomposition for Designing Closed-loop Supply Chain Network Design under Uncertainty

نویسنده [English]

  • Aliakbar Hasani
چکیده [English]

In this paper, a comprehensive mathematical model for designing supply chain network via considering integrated flow of forward and reverse of multiple products during multiple periods is proposed. The uncertainty of the parameters includes customer demand, products reverse flows, rates of reverse product recovery and disposal, as well as costs of products transportation, storage and reverse flow management are considered via two stage stochastic programming. An efficient solution algorithm based on the sample average approximation and new accelerated benders decomposition is developed to solve the proposed model. An accelerated Benders decomposition algorithm utilizing efficient acceleration mechanisms based on the priority heuristic and adding the demand constraint to master problem is devised to cope with computational complexity. Computational analysis is also provided by using a phone cell industrial case study to present the significance of the proposed stochastic model versus deterministic one as well as the efficiency of the proposed the accelerated benders decomposition algorithm. In addition, obtained solutions of the stochastic model have a more robustness than solutions of the deterministic model.

کلیدواژه‌ها [English]

  • Supply chain network design
  • Closed-loop
  • Uncertainty
  • Stochastic programming
  • Benders decomposition
  • Sample average approximation
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