Optimal Decision on Pricing and Replenishment of Vegetable Products Based on Goal Planning
DOI:
https://doi.org/10.54097/pa5cxv70Keywords:
Normality test, Spearman correlation analysis, Lasso regression, ARIMA model, Single objective planning.Abstract
Developing replenishment and pricing plans has always been the key for fresh food supermarkets to gain more profits. This paper analyzes various situations and provides the optimal solution through Spearman correlation analysis, Lasso regression, goal programming and other methods and models. We use normality testing and box plots to present the distribution patterns of major categories and individual products from both vertical and horizontal perspectives. Establish a single objective programming model and solve it with Lingo to obtain a maximum profit of 98513 yuan for 7 days. The largest total replenishment amount is for the flower and leaf category, the smallest is for edible mushrooms, the highest average cost markup rate is for aquatic roots and stems, and the lowest is for cauliflower. This has certain reference value and theoretical significance for fresh food supermarkets to formulate replenishment and pricing plans.
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