Research On Replenishment Strategy Of Vegetable Commodities Based On Linear Programming And Multi-Objective Particle Swarm Optimisation Algorithm

Abstract

Because vegetable commodities are characterised by shorter freshness periods and diminishing character, they need to be replenished and priced on a daily basis based on historical sales and demand. In order to determine the optimal order quantity and sales price of vegetable commodities, this paper uses the least squares method to establish a regression model to obtain the relationship between sales volume and cost-plus pricing equation and verify the fitting effect, and then the total sales volume of the category obtained from the regression model and the cost-plus pricing equation combined with the derivation of the profit, the establishment of the optimisation model, the solution to obtain the replenishment volume and pricing strategy that will maximise the profitability of the superstore in the coming week. Considering the restricted situation of commodity categories, this paper chooses 0-1 integer planning,and adopts the multi-objective particle swarm optimisation algorithm to solve the optimisation model, and then iteratively calculates to get the global optimal solution, so as to find out the daily replenishment quantity of a single product and pricing strategy which will make the supercommercial supermarket have the largest revenue on 1 July.