Title :
A Genetic Algorithm Based Approach For Mixed-Media Advertising Budgeting
Author :
Ying, Sun ; Zhizhong, Mao
Author_Institution :
Sch. of Inf. Sci. & Eng., Northeastern Univ. Shenyang, Shenyang, China
Abstract :
Mixed-media advertising which has become more effective and popular attracts the attention of advertising agencies, media planners and advertisers. How to decide and allocate the budget for mixed-media advertising becomes a fundamental part of a company´s advertising campaign.In this paper, an optimization approach based on Genetic Algorithm is proposed to deal with this advertising budget problem which is formulated as a constrained nonlinear programming problem. Then an experiment example is given to explain the process of our approach. The result of this example supports the feasibility and efficiency of our method.
Keywords :
advertising; budgeting; genetic algorithms; advertising agencies; genetic algorithm based approach; media advertisers; media planners; mixed-media advertising budgeting; nonlinear programming problem; optimization approach; Advertising; Constraint optimization; Genetic algorithms; Genetic engineering; Information science; Intelligent systems; Marketing and sales; Sun; Thumb; Vehicles;
Conference_Titel :
Intelligent Systems, 2009. GCIS '09. WRI Global Congress on
Conference_Location :
Xiamen
Print_ISBN :
978-0-7695-3571-5
DOI :
10.1109/GCIS.2009.47