Goal programming model for predicting the parameters involved in growth of cancer cells

Jayabharathiraj, J.

doi:10.1504/ijor.2019.10019741

Cited by 1 publication

(1 citation statement)

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“…Combined with the prediction of daily wholesale price and sales volume of each category in the coming week by the above model, the total daily sales volume of each category of vegetables under different sales unit prices can be obtained by substituting different sales unit prices. In order to formulate the maximum revenue strategy, it is necessary to define the linear optimization function [11] in combination with the goal planning problem [10] (because the wholesale price, total sales volume, sales unit price and profit are linear relationships). The specific standard calculation formula is as follows.…”

Section: Daily Replenishment-pricing Strategy For Different Vegetablesmentioning

confidence: 99%

Replenishment Strategy Model Based on Cost-plus Pricing

Huang,

Zhang

2024

HSET

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To formulate the commodity pricing replenishment strategy to meet the short-term profit demand of merchants, we established a pricing replenishment prediction model based on the sales-cost-plus pricing correlation. It integrates four-dimensional profit factors, taking the maximization of total profit as the core guidance and considering the objective impact of date. With ARIMA and random forest algorithm, the commodity cost and sales volume are predicted from the perspective of sales cyclical fluctuation. Finally, we constructed the optimal pricing linear function based on the goal programming problem. The optimal pricing replenishment strategy can be determined by adjusting the commodity pricing. The calculation results show that the prediction accuracy of the model is higher than 0.71, which can provide merchants with pricing and replenishment strategies with high reliability.

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Section: Daily Replenishment-pricing Strategy For Different Vegetablesmentioning

confidence: 99%