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

Abstract

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.

Keywords

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