نوع مقاله : مقاله پژوهشی

نویسنده

استادیار، دانشگاه صنعتی شاهرود.

چکیده

در جهان پیچیده امروزی و به­‌منظور افزایش رقابت‌­پذیری، توجه برنامه­‌ریزان در بخش سیستم­‌های تولیدی به مقوله توزیع محصولات و جمع‌آوری محصولات استفاده‌­شده افزایش یافته است. در این پژوهش، مسئله زمان­بندی زنجیره تأمین حلقه‌­بسته برای نخستین بار بررسی می­‌شود. یک مدل جامع و یکپارچه در خصوص زمان­بندی تولید محصولات، ارسال بسته‌­ای آن­ها به مشتریان توسط وسایل حمل‌ونقل با ظرفیت محدود و جمع­‌آوری محصولات استفاده­‌شده از محل مشتریان و بازگرداندن آن­ها به محل کارخانه برای انجام فرآیند بازیافت ارائه می‌­شود. هدف این مسئله، کمینه‌­کردن حداکثر زمان تأخیر در تحویل محصولات است. با توجه به NP-hard­ بودن مسئله، برای حل مسائل بزرگ یک الگوریتم ژنتیک ارائه می­‌شود که قادر است جواب­‌هایی نزدیک به جواب بهینه ایجاد کند. برای بیان میزان اهمیت مسئله موردبررسی در این پژوهش، یک مطالعه موردی مربوط به زنجیره تأمین روغن‌­موتور ارائه می‌شود.

کلیدواژه‌ها

عنوان مقاله [English]

An Optimization Model for Closed-Loop Supply Chain Scheduling Problem

نویسنده [English]

  • Mohammad Rostami

Assistant Professor, Shahrood University of Technology.

چکیده [English]

In today's complex world and in order to increase competitiveness, planners in the manufacturing systems have focused on product distribution and collection of used products. In this paper, the closed-loop supply chain scheduling problem is investigated for the first time. A comprehensive and integrated model is presented for production scheduling, delivering products to retailers using limited-capacity vehicles, and pick-upping end of life products in order to recycle and reuse in supply chain. The aim of this problem is to minimize maximum tardiness. Due to the fact that this problem is NP-hard, a genetic algorithm is presented to solve the large-size instances by obtaining near-optimal solutions. To illustrate the importance of the problem under consideration, a case study of the motor oil supply chain is presented.

کلیدواژه‌ها [English]

  • Scheduling
  • Closed-Loop Supply Chain
  • Maximum Tardiness
  • Linear Programming Model
  • Genetic Algorithm
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