ارائة نوعی مدل تصمیم جدید در برنامه‌ریزی تبلیغات اینترنتی با استفاده از الگوریتم ژنتیک چندهدفه

نوع مقاله: مقاله علمی پژوهشی

نویسندگان

1 دانشیار دانشکدة مدیریت و اقتصاد، دانشگاه شهید باهنر، کرمان، ایران

2 کارشناس‌ارشد مدیریت بازرگانی، دانشکدة مدیریت و اقتصاد، دانشگاه شهید باهنر، کرمان، ایران

3 کارشناس‌ارشد مدیریت اجرایی دانشکدة مدیریت و اقتصاد، دانشگاه شهید باهنر، کرمان، ایران

چکیده

امروزه افزایش پیچیدگی مسائل و مدل‌های بازاریابی به استفاده از راه‌حل‌های پیچیده منجر شده است. به‌کارگیری روش‌های نوین در برنامه‌ریزی بازاریابی و تبلیغات در کانون توجه پژوهشگران این حوزه قرار گرفته و موجب افزایش استفاده از روش‌های فرا ابتکاری مبتنی بر محاسبات تکاملی و هوش مصنوعی شده است. در این رابطه، بر اساس ویژگی‌های تبلیغات از طریق وب و راهبردهای قیمت‌گذاری موجود، راهبرد قیمت‌گذاری ترکیبی مبتنی بر متغیرهای «هزینه برحسب هزار بار نمایش» و «هزینه برحسب هر کلیک در این پژوهش» ایجاد شد. متعاقب آن، مدل تصمیم بهینه‌سازی چندهدفة جدید بر مبنای این راهبرد مطرح گردید. در این مدل، منافع مدیران وب‎سایت‌ها و متقاضیان ارائة تبلیغات مد نظر قرار گرفته است. از آنجا که مدل جدید، یک مدل بهینه‌سازی چندهدفه با ابعاد بالاست، از الگوریتم بهینه‌سازی ژنتیک چندهدفه برای حل آن استفاده شده است. در پایان، با ارائۀ مثال محاسباتی و نتایج عددی شبیه‌سازی، اثربخشی مدل و الگوریتم ثابت می‎شود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Providing a New Decision Model in Internet Advertising Planning Using Non-dominated Sorting Genetic Algorithm II

نویسندگان [English]

  • Mahdi Ebrahimi 1
  • Mohammadreza Namdar 2
  • Marjan Tavasolifard 3
1 Associate Prof., Faculty of Management and Economics, Shahid Bahonar University of Kerman, Iran
2 M.Sc. in Business Management, Shahid Bahonar University of Kerman, Iran
3 M.Sc. in Executive Management, Shahid Bahonar University of Kerman, Iran
چکیده [English]

Today, marketing models and issues are increasingly becoming complex, leading to the use of complicated solutions. The application of novel methods in marketing and advertising planning is of interest to researchers of these fields. This has led to an increase in utilization of meta-heuristics based on evolutionary computations and artificial intelligence. Regarding web advertising characteristics and current pricing strategies, in this article a hybrid pricing strategy was created based on variables of Cost-per-thousand-impressions (CPM) and Cost-per-click (CPC). Consequently, the new multi-objective optimization decision model was proposed based on this strategy. This model considered the interests of both websites managers and web advertisers. Since this new model is a high dimensional multi-objective optimization model, Non-dominated Sorting Genetic Algorithm II (NSGA-II) was used to solve it. At last, a computational example was used and numerical results obtained from the simulation proved the effectiveness of the model and algorithm.

کلیدواژه‌ها [English]

  • Hybrid pricing
  • Multi-Objective Optimization
  • Non-dominated Sorting Genetic Algorithm II (NSGA-II)
  • Wed advertising
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