Research On Optimization Of Picking Path Of Company Y Based On Ant Colony Algorithm

In recent years,the gradual rise of E-commerce,while injecting more energy into the retailing,has also brought inevitable challenges to it.The emerging sales model can help the traditional retail industry to expand sales channels and break the multiple barriers of time and space,but at the same time also need to pay certain infrastructure construction costs.For example,the construction of logistics facilities creates more possibilities for retail enterprises,but it also brings cost issues that cannot be ignored.For most retail enterprises,logistics costs are the second largest expenditure after production costs.Therefore,reducing logistics costs has become an important breakthrough for retail companies to achieve cost control while ensuring product quality.The logistics services required by the retail industry are mainly divided into two parts:warehousing and transportation.Among them,the warehousing and picking operation workload accounts for 60%,the operation time accounts for 30%to 40%,and the picking mobile cost accounts for the overall warehousing about 90%of the operating cost.It can be seen that the picking operation is an important link in the logistics service,and the workload and working time occupied by this link can not be ignored,and scientific and reasonable planning of the picking path can effectively reduce its moving costs,which is to solve the picking operation effective methods and means of low efficiency and high cost^[49].Y company is a city warehouse and distribution company in Dalian,which is responsible for the retail commodity storage services of more than 40 suppliers,as well as the retail commodity distribution of large supermarkets,medium and small stores and catering companies.In this research,with the shortest picking path as the goal,the picking path optimization model of Y company was established,and the model was solved by ant colony algorithm.In the end,the distance of the picking paths between before and after optimization is compared to verify the effectiveness of the optimization in this study.This study first sorts out the theories related to urban distribution and picking routes,clarifies the important influence of picking route planning on the operational efficiency and cost control of urban distribution enterprises,and then raises research questions.According to the questions to compare pros and cons of each heuristic algorithm,choose the ant colony algorithm to calculate the Y company picking path model,and explain the ant colony algorithm related theory and its calculation steps.Furthermore,taking the picking operation as the core,the company Y's operation status is analyzed,and the outstanding problems urgently to be solved in the Y company's picking operation are pointed out.Finally,according to the storage layout of Y company and the actual situation of picking operations,a mathematical model of the picking path and a TSP model combined with ant colony algorithm are constructed to discuss the impact of important parameters of the ant colony algorithm on the algorithm performance and optimization results.On this basis,according to algorithm performance and results to debug parameters through C++.After the parameters are determined,the model is calculated through C++programming,and the optimized picking path plan is obtained.The distance between the picking path before and after optimization is compared.Verify the effectiveness of the optimization plan in this study.The research results obtained in this paper can not only solve the problem of Y company's picking path optimization,but also provide a reference for other similar companies'picking path optimization problems.