Applying Multi-Objective Genetic Algorithms for Optimal Internet Advertisement Purchase

• Main Authors: Yu-Hsien Chen, 陳有賢
• Other Authors: Chao-Chang Chiu
• Format: Others
• Language: en_US
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/97829754828882188205

碩士 === 元智大學 === 資訊管理研究所 === 91 === It is able to directly interaction with customer and the fee lower then traditional media when the companies want to make more benefit by advertising in the Internet. However, most advertisers who purchase media of cyberspace via advertise agency. There are some problems that one is the media planner of advertising agency proceed media mix plan just use the click rate of web site or use fix index about operator web site. Second is the survey data always not coincidence that published by each web site. So our research attempts to solve the problems of advertisement purchase optimization. Advertisement purchase optimization means finding a portfolio of advertisement purchase that the enterprise will gain the greatest benefit. First, we establish the advertisement purchase optimization model based on the survey data of website that provide by one specific marketing survey company and information form advertisement analysis of advertiser. In order to solve such optimization problem with multiple objectives, we apply multiple-objective optimization to solve the advertisement purchase optimization model. The optimization technique of multiple-objective optimization we apply is multi-objective genetic algorithm.