Abstract

Optimization of Products Shelf Space Allocation Based on Product Price Using Multilevel Association Rules. Product allocation, product assortment, and product price have a significant influence on customer buying behavior. With limitation on shelf space, retailer must select, pricing, and allocate the products on shelf space optimally to maximize the profit for retailer. This research is focused on optimizing the products shelf space allocation based on the relationship between product categories and product price using data mining technique, multilevel association rules. Takes advantage of data transactions, 9 associations between categories, 24 associations between subcategories, and 67 associations between products were obtained. By using zero one integer programming selected 61 products with appropriate price that must be maintained to be allocated in the minimarket to maximize the retailer’s profit. The result, product allocation configuration based on the relationship between product categories and product price is shown. Keywords: Product Allocation, Data Mining, Multilevel Association Rules, Zero One Integer Program, Pricing

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