برنامه‌ریزی تصادفی دومرحله‌ای برای طراحی شبکه زنجیره تأمین دارویی بهنگام: مدل‌سازی و الگوریتم حل

نوع مقاله : مقاله پژوهشی

نویسندگان

1 کارشناسی ارشد، دانشگاه بوعلی سینا.

2 دانشیار، دانشگاه بوعلی سینا.

چکیده

دارو محصولی حیاتی است که سلامت جامعه را رقم می­‌زند و تحویل به‌موقع آن به مصرف‌­کنندگان از اهمیت بالایی برخوردار بوده و در نتیجه نیازمند به برنامه‌­ریزی مناسبی برای تولید/توزیع آن هستیم. در این پژوهش یک مسئله زنجیره‌­تأمین دارویی دوسطحی چند­دوره‌ای ارائه شد که تقاضا در سطح دوم غیرقطعی است. برای مدل‌سازی مسئله یادشده از رویکرد برنامه‌ریزی تصادفی دومرحله‌ای استفاده شد. هدف مدل ارائه­‌شده شامل حداقل‌­کردن هزینه‌­های تولید، موجودی، انتقال، هزینه‌های زمان ارسال، زودکرد و دیرکرد است. با توجه به اینکه مدل با تابع هدف زودکرد و دیرکرد با موعد تحویل متفاوت یک مسئله NP-hard است و هرچه ابعاد مسئله افزایش یابد، روش دقیق توانایی حل مسئله را در زمان معقول ندارد؛ بنابراین برای این مسئله یک الگوریتم ژنتیک به همراه یک الگوریتم ترکیبی ژنتیک و جست­وجوی همسایگی متغیر ارائه شد. در حل این مدل با استفاده از برنامه‌­ریزی تصادفی، پنج سناریو مطالعه و شاخص «ارزش مورد­انتظار اطلاعات کامل» محاسبه و درنهایت نتایج آن با جواب مدل برنامه‌­ریزی تصادفی دومرحله‌ای مقایسه شد. همچنین روش برنامه‌ریزی تصادفی، الگوریتم ترکیبی و الگوریتم ژنتیک در ­نظر ­گرفتن سناریوهای مختلف با یکدیگر مقایسه شدند. نتایج نشان داد که از لحاظ تابع هدف الگوریتم ترکیبی کارایی بسیار خوبی در مقایسه با الگوریتم ژنتیک دارد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Stochastic Bilevel Programing to Design of A JIT Pharmaceutical Supply Chain Network: Modeling and Algorithm

نویسندگان [English]

  • Maryam Hajibabaie 1
  • Javad Behnamian 2
1 Msc, Bu-Ali Sina University.
2 Associate Professor, Bu-Ali Sina University.
چکیده [English]

In the pharmaceutical supply chain, pharmaceutical products must be distributed among consumers with good quality at the right time and in the right place. Medicineis a product which affects the health of society and its timely delivery to consumers is of great importance. Therefore, it requires proper planning for its production and distribution. In this paper, we developed a model that minimize the cost of production, inventory, delivery, earliness and tardiness. We also assumed the uncertainty of demand and solved the linear mathematical model using stochastic programming and we solved the problem with stochastic programming. Also, due to the fact that the model with the objective function of earliness and tardiness with different delivery times of NP-hard problem for this problem, a hybrid genetic and variable neighborhood search algorithm were presented. Here, five scenarios were considered, the expected value of perfect information (EVPI) was measured and the obtained results were compared with the two-stage random-scheduling model. The computational results showed the efficiency of the developed model. Also, the results of the proposed hybrid algorithm were compared with the genetic algorithm, and the results showed that in terms of objective function, the hybrid algorithm has a much better performance compared to the genetic algorithm.

کلیدواژه‌ها [English]

  • Pharmaceutical Supply Chain؛ Stochastic Programming؛ Hybrid Algorithm؛ Just-In-Time
  • Genetic Algorithm

مراجع

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