Research on Inventory Optimization of E-Commerce Retail Merchants Based on Improved Genetic Algorithm
Inventory optimization refers to reducing the cost of inventory system by considering the factors of order point and delivery time to deal with the uncertainty of demand.This paper first constructs a math-ematical planning model,taking the safety inventory level strategy(s,S)and daily replenishment volume as the core decision variables,with the goal of minimizing the total inventory cost(holding and out costs)and the ordering cost of inventory turnover days.Then 0-1 auxiliary variables are introduced to linearize the nonlinear constraints,and Gurobi and COPT solvers are used to numerically analyze and compare the models.At the same time,the application of genetic algorithm in inventory optimization is further pro-posed,and a novel coding method is designed in a pioneering way to effectively enhance the efficiency and accuracy of solution.The example shows that this inventory optimization reduces the demand uncertainty,flexibly responds to multiple demand patterns in retail demand,and combines the(s,S)policy with the op-timized inventory holding and order quantity to achieve the lowest inventory cost and the number of inven-tory turnover days,and finally realizes efficient inventory management and purchasing decisions.
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