Fleming, P.J. and Pashkevich, M.A. (2007) Optimal advertising campaign generation for multiple brands using MOGA. IEEE Transactions on Systems Man and Cybernetics Part C, 37 (6). pp. 1190-1201. ISSN 1094-6977
The paper proposes a new modified multiobjective genetic algorithm (MOGA) for the problem of optimal television (TV) advertising campaign generation for multiple brands. This NP-hard combinatorial optimization problem with numerous constraints is one of the key issues for an advertising agency when producing the optimal TV mediaplan. The classical approach to the solution of this problem is the greedy heuristic, which relies on the strength of the preceding commercial breaks when selecting the next break to add to the campaign. While the greedy heuristic is capable of generating only a group of solutions that are closely related in the objective space, the proposed modified MOGA produces a Pareto-optimal set of chromosomes that: 1) outperform the greedy heuristic and 2) let the mediaplanner choose from a variety of uniformly distributed tradeoff solutions. To achieve these results, the special problem-specific solution encoding, genetic operators, and original local optimization routine were developed for the algorithm. These techniques allow the algorithm to manipulate with only feasible individuals, thus, significantly improving its performance that is complicated by the problem constraints. The efficiency of the developed optimization method is verified using the real data sets from the Canadian advertising industry.
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|Institution:||The University of Sheffield|
|Academic Units:||The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)|
|Depositing User:||Sherpa Assistant|
|Date Deposited:||18 Dec 2007 16:44|
|Last Modified:||08 Feb 2013 16:55|