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户外广告资源配置优化模型及算法研究
引用本文:朱军,陈敬良,张安淇.户外广告资源配置优化模型及算法研究[J].上海理工大学学报,2019,41(2):190-195.
作者姓名:朱军  陈敬良  张安淇
作者单位:上海理工大学 管理学院, 上海 200093,上海理工大学 管理学院, 上海 200093,复旦大学 管理学院, 上海 200433
基金项目:教育部人文社会科学研究青年基金资助项目(16YJCZH165)
摘    要:针对户外媒体广告的特点,提出了一个户外广告资源配置优化模型,将其建模为一个带约束的整数优化问题,最大化户外广告的总收益。通过罚函数法进行约束处理,提出了一种协同混合粒子群算法进行求解,仿真结果表明了该算法的有效性。将这种模型运用于户外广告进行综合定价,能够较好地解决广告主和相关广告运营企业的共同利益互存,使双方的利益最大化。

关 键 词:户外广告  粒子群算法  引力搜索算法  协同混合粒子群  定价策略
收稿时间:2018/10/25 0:00:00

Modeling and Algorithm for Outdoor Advertising Resources Optimization
ZHU Jun,CHEN Jingliang and ZHANG Anqi.Modeling and Algorithm for Outdoor Advertising Resources Optimization[J].Journal of University of Shanghai For Science and Technology,2019,41(2):190-195.
Authors:ZHU Jun  CHEN Jingliang and ZHANG Anqi
Institution:Business School, University of Shanghai for Science and Technology, Shanghai 200093, China,Business School, University of Shanghai for Science and Technology, Shanghai 200093, China and School of Management, Fudan University, Shanghai 200433, China
Abstract:According to the properties of outdoor advertising, a pricing strategy model was proposed based on location based service and big data. It was modeled as a constrained integer optimization model to maximize the total revenue of operators. An improved particle swarm optimization was proposed for solving the outdoor advertising optimization problem, using the penalty function method for constraint handling. The simulation results show the validity of the algorithm. Applying this model to outdoor advertising for comprehensive pricing can better solve the common interests of advertisers and relevant advertising operators, and maximize the interests of both parties.
Keywords:outdoor advertising  particle swarm optimization  gravitational search algorithm  cooperative hybrid particle swarm  pricing strategy
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