Predictive Model for Successful Product Mix in Trade Outlets using Genetic Algorithm and Association Rule Mining
About this article
DOI:
https://doi.org/10.14419/ijet.v7i4.19.22101Keywords:
Association-mining, Apriori, Binary-Encoding, Genetic-AlgorithmsAbstract
Supermarket chains seem to be have a humongous amount of data. Aprioi algorithm is considered to be the classic way to create associations in the data and create power combination of products that would occupy a particular shelf and area. This algorithm employs the greedy method to create meaningful associations between data. This mechanism, however , has a very high time complexity. Its time complexity is linearly proportional to the product of number of transactions and the average number of products bought per transaction, thus creating computations that can only be solved in polynomial time when compared to the logarithmic-time complexity algorithm which we employ in this paper.
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