Research On Green Inventory Routing Problem Optimization Based On VMI

With the intensification of market competition,companies have begun to seek strategic cooperation with other companies in the supply chain.The vendor managed inventory that can effectively alleviate the bullwhip effect and reduce overall operating costs has gradually attracted the attention of companies.For enterprises,the key to implement VMI is to jointly optimize inventory management and distribution decisions.At the same time,countries all over the world are paying more and more attention to the issue of energy conservation and emission reduction.When making various decisions,enterprises should respond to the country's call for green and environmental protection,and take into account the impact of actual production and operation activities on the environment.In this context,the green inventory routing problem arises.The green inventory routing problem is a further extension of the traditional inventory routing problem.It reduces CO₂ emissions from transportation vehicles while jointly optimizing inventory management and distribution decisions.It is a comprehensive optimization that considers the impact of inventory management,vehicle routing and logistics activities on the environment problem.Based on VMI,this paper studies the single-category,and multi-period green inventory routing problem under random demand,and constructs non-linear mixed integer programming model that takes minimizing inventory cost,and distribution cost as objective function,vehicle load,retailer inventory capacity,etc.as restrictions.When calculating the distribution cost,the carbon emission cost is used as a decision-making factor,and a comprehensive emission model is selected to measure vehicle fuel consumption,taking into account the impact of vehicle speed and load on fuel consumption and CO₂ emissions in different road sections.Aiming at the problem that the replenishment strategy of retailers during the entire planning period will not be changed after the formulation,and the multi-period optimization early decision will affect the later period,it is difficult to find the optimal solution to ensure the lowest cost during the entire planning period.This paper designs the hybrid heuristic algorithm of genetic algorithm nested particle swarm algorithm is used to solve the problem,and the effectiveness of the optimization model and algorithm is proved through a calculation example.At the same time,the calculation example is compared with the inventory routing model that does not consider CO₂ emissions to verify the necessity of considering the cost of CO₂ emissions in the process of making inventory distribution decisions.Finally,the multi-category green inventory routing problem is studied.It is pointed out that direct calculation according to the replenishment strategy may cause the total inventory of all products to exceed the maximum storage capacity of retailer warehouse.And then method for calculating the replenishment volume of multi-category products based on demand with the maximum storage capacity as the limit and the minimum out-of-stock cost as the decision goal is proposed.Model solving continues to use the hybrid heuristic algorithm which further expands the scope of application of the algorithm.