Ads manager platform gains popularity among numerous e-commercial vendors/advertisers. It helps advertisers to facilitate the process of displaying their ads to target customers. One of the main challenges faced by advertisers, especially small and medium-sized enterprises, is to configure their advertising strategy properly. An ineffective advertising strategy will bring too many ``just looking'' clicks and, eventually, generate high advertising expenditure unproportionally to the growth of sales. In this paper, we present a novel profit-maximization model for online advertising optimization. The optimization problem is constructed to find optimal set of features to maximize the probability that target customers buy advertising products. We further reformulate the optimization problem to a knapsack problem with changeable parameters, and introduce a self-adjusted algorithm for finding the solution to the problem. Numerical experiment based on statistical data from Tmall show that our proposed method can optimize the advertising strategy given expenditure budget effectively.

翻译：广告经理平台在众多电子商业销售商/广告商中受到欢迎。 它帮助广告商为向客户展示广告广告的进程提供便利。 广告商,特别是中小企业面临的主要挑战之一是适当配置广告战略。 无效的广告战略将带来太多的“光看”点击,并最终产生与销售增长不成比例的高额广告支出。 在本文中,我们为在线广告优化提供了一个新的利润最大化模式。 优化问题的构建是为了找到一套最佳功能,以尽可能扩大客户购买广告产品的概率。 我们进一步将优化问题改写为可修改参数的knapack问题,并引入一个自行调整的算法,以找到问题的解决方案。 基于Tmall统计数据的量化实验显示,我们提出的方法可以有效地优化给支出预算的广告战略。