طراحی یک زنجیره‌تأمین‌ چهار سطحی دارو با در نظر گرفتن اهداف اقتصادی، اجتماعی و رضایت مناطق

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشیار گروه مهندسی صنایع، مدیر فناوری اطلاعات دانشگاه قم

2 دانشجوی کارشناسی ارشد مهندسی صنایع، دانشکده فنی و مهندسی، دانشگاه قم، قم، ایران

3 کارشناس ارشد مهندسی صنایع، دانشکده فنی و مهندسی، دانشگاه صنعتی قم، قم، ایران

چکیده

در این مقاله یک مدل جدید برنامه‌ریزی چندهدفه برای طراحی یک شبکه زنجیره­تأمین‌‌ چهار سطحی دارو در چند دوره و برای چند محصول فاسدشدنی توسعه داده می­شود. سطوح زنجیره شامل تأمین‌‌کنندگان، تولیدکنندگان، مراکز توزیع و خرده‌فروشان است. این مدل به تصمیم­گیری یکپارچه مسائل مکان­یابی­ مراکز تولید و مراکز توزیع دارو، تخصیص بهینه آن‌ها به یکدیگر به‌منظور حمل‌ونقل مناسب داروها در بین سطوح، تعیین مقدار بهینه­ی تولید و حمل‌ونقل در بین تسهیلات و نیز تعداد بهینه­ی استخدام و اخراج نیروی کار برای تولید بهینه محصولات دارویی کمک می­کند. همچنین مراکز تولید و توزیع دارای سطح تکنولوژی مختلف جهت تأسیس هستند. اهداف مسئله شامل کاهش هزینه­های زنجیره همراه با کاهش اختلاف بیکاری و تأمین‌ دارو در بین مناطق مختلف و افزایش رضایت مناطق مختلف با توجه به اهمیت تأمین‌ هرچه بیشتر دارو است. به‌دلیل NP-hard بودن مسئله و عدم کارایی روش­های دقیق، یک روش فراابتکاری مبتنی بر الگوریتم ژنتیک برای حل مسئله معرفی و عملکرد آن در طیف گسترده­ای از مسائل نمونه­ای تک­هدفه و دوهدفه بررسی می­شود. نتایج نشان می­دهد وجود هدف بیشینه کردن رضایت مناطق و کاهش اختلاف آن بین مناطق مختلف اهمیت بالایی در زنجیره­تأمین‌‌ دارو دارد. علاوه بر آن، کاهش اختلاف بیکاری بین مناطق مختلف باعث بهبود سطح اشتغال و وجود تعادل در مسئولیت­های اجتماعی زنجیره می­شود. همچنین الگوریتم پیشنهادی قادر است مسائلی با سایز بزرگ را هم به‌صورت تک­هدفه و هم دوهدفه درزمانی کم و جوابی کارا حل کند

کلیدواژه‌ها


عنوان مقاله [English]

A four-echelon supply chain considering economic, social and regions satisfaction goals

نویسندگان [English]

  • Jalal Rezaeenour 1
  • Motahhare Hashempoor 2
  • Amir Hosein Akbari 3
1 Assistant professor, Department of Industrial Engineering, Faculty of Technology and Engineering, University of Qom, Head of ICT Center, University of Qom
2 MSc student, Department of Industrial engineering, university of Qom, Qom, Iran
3 MSc, Department of Industrial engineering, qom university of technology, Qom, Iran
چکیده [English]

This study develops a new multi-objective programming model to design a four-echelon pharmaceutical supply chain (PSC) network for several perishable products over multiple time periods. Supply chain consists of four echelons, including suppliers, manufacturers, distribution centers, and retailers. This model proposes an integrated decision-making approach for the location of facilities (pharmaceutical production and distribution sites) and their most suitable allocation to each other for a reliable transportation of products between echelons. It also determines the optimal amount of production and transportation among facilities and the required number of labours. A varying level of technological expertise is required for the establishment of production and distribution systems. The problem aims to reduce costs and unemployment and pharmaceutical supply gap between regions and to increase their satisfaction rate with an emphasis on the importance of providing a large supply of pharmaceutical products. Given the fact that the problem is a NP-hard one and accurate methods are inefficient, a genetic algorithm-based meta-heuristic is developed for problem-solving and its performance is analyzed on a wide range of single- and two-objective problem instances. The results show that an increase in the satisfaction rate of regions and a reduction in its gap between regions as two objectives are of great importance in pharmaceutical supply chain. Moreover, a reduction in unemployment gap between regions improves the level of employment, and it provides a right balance between social responsibilities. The developed algorithm also provides an optimal solution for large-sized single- and two-objective problems in a short time period.

کلیدواژه‌ها [English]

  • Pharmaceutical Supply Chain
  • Sustainable Development
  • Social Responsibility
  • Genetic Algorithm
  • Social Inequality
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