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。
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.
作者
朱军
陈敬良
张安淇
ZHU Jun;CHEN Jingliang;ZHANG Anqi(Business School,University of Shanghai for Science and Technology,Shanghai 200093,China;School of Management,Fudan University,Shanghai 200433,China)
出处
《上海理工大学学报》
CAS
CSCD
北大核心
2019年第2期190-195,共6页
Journal of University of Shanghai For Science and Technology
基金
教育部人文社会科学研究青年基金资助项目(16YJCZH165)
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
outdoor advertising
particle swarm optimization
gravitational search algorithm
cooperative hybrid particle swarm
pricing strategy
