انتخاب استراتژی‌های بازاریابی زنجیره تأمین در شرایط انتشار عدم‌قطعیت

نوع مقاله : مقاله پژوهشی

نویسنده

استادیار، دانشگاه صنعتی شاهرود.

چکیده

در این مقاله، یک زنجیره تأمین حلقه‌ بسته با هدف پاسخگویی به تقاضای مشتریان و ارائه خدمات پس­ازفروش با حداکثر سود ممکن بررسی شده است. عدم­قطعیت پارامترهای تقاضای مشتریان و ظرفیت تسهیلات از طریق تابع توزیع احتمال پیوسته درمدلاعمالشده ومسئلهبهروش برنامه‌ریزیتصادفیودرغالب یکمدلبرنامه‌ریزی غیرخطی عددصحیحمختلط، فرمول‌بندیشدهاست؛ علاوه بر آن انتشار عدم‌قطعیت بین سطوح زنجیره تأمین در نظر گرفته شده و تأثیر آن بر سطح پاسخگویی به تقاضای مشتریان نیز ارزیابی شده است. همچنین، امکان انتخاب بهترین استراتژی بازاریابی برای زنجیره تأمین و ایجاد یک جریان قابل‌اطمینان در طی دوره برنامه‌ریزی لحاظ شده است. مدل ارائه‌شده با استفاده از یک الگوریتم ممتیک مبتنی بر الگوریتم‌های ژنتیک و جست­وجوی همسایگی متغیر انطباق‌پذیر حل شده است. کارایی الگوریتم حل با مقایسه عملکرد آن با دو الگوریتم فراابتکاری دیگر ارزیابی شده است. مدل و روش حل ارائه‌شده برای یک مسئله نمونه در صنعت تولید موتور خودرو اجرا شده است؛ درنهایت مجموعه‌ای از توصیه‌های مدیریتی با توجه به تحلیل نتایج و یافته‌های تحقیق پیرامون همبستگی و تأثیرات متقابل استراتژی‌های بازاریابی مدنظر ارائه شده است. نتایج، حاکی از تأثیر چشمگیر انتشار عدم‌قطعیت بر برنامه‌ریزی در سطح زنجیره تأمین و عملکرد و اندرکنش متفاوت هر یک از استراتژی‌های بازاریابی مدنظر است.

کلیدواژه‌ها

عنوان مقاله [English]

Marketing Strategies Selection for Supply Chain Management under Uncertainty Propagation

نویسنده [English]

  • Aliakbar Hasani
Faculty member, Shahrood University of technology.
چکیده [English]

In this paper, we consider a closed-loop supply chain supplying products to markets and an after-sales supply chain providing spare parts to fulfill after-sales commitments. Uncertainties of product demand and facility capacity are considered via using continuous probability distribution function and are formulated in the form of a nonlinear mixed integer programming model. In addition, marketing strategies selection for supply chain management and reliable flow creation during the planning periods are considered. Here, we propose a comprehensive mathematical model for determining the best marketing strategies and preserving reliable flow dynamics throughout the chains’ networks. A new memetic algorithm is developed that incorporates genetic algorithm and adaptive variable neighborhood search to find the best solutions. Efficiency of the proposed memetic algorithm is evaluated by comparing its performance with two other solution algorithms. The proposed model and its solution approach are tested using data from an engine production company. We derive some managerial insight by analyzing the correlations among the marketing strategies and how they affect each other.

کلیدواژه‌ها [English]

  • Marketing Strategies Selection؛ Uncertainty Propagation
  • Memetic Algorithm

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