Study On Material Distribution Path Optimization Of Assembly Shop In R Company

With the continuous development of manufacturing enterprises,the improvement of the in-plant logistics system has gradually become a key point for enterprises to improve economic efficiency.As part of the in-plant logistics,the workshop material distribution system determines whether the production line can operate normally or not.The timely and efficient material distribution system is of great significance for achieving lean production.Reasonable material distribution path plan is not only the precondition of meeting the demand of production lines' raw materials,but also to facilitate the timely delivery of materials.The optimization of the material distribution path of the workshop plays an important role in improving production efficiency,saving costs and enhancing the competitiveness of the same industry.This paper studies the problem of material distribution of the assembly shop in R company.Firstly,after analyzing the current situation of material distribution of the company,this paper has clarified the existing problems and research significance.In order to reduce the total delivery time and improve the delivery effect of just in time,this paper establishes the material distribution path optimization model of dual targets with mixed time window with the aim of minimizing the total delivery time and penalty cost of time window.Model contains constrains such as delivery time window and maximum load capacity of the vehicle.Then,through comparative analysis of the relevant theory solving material distribution path optimization problems,this paper selects the genetic tabu search algorithm as the optimization method of model.Finally,using MATLAB simulation,the genetic algorithm is used to optimize the material distribution path of the 45 demand points in the assembly shop.Compared with the schemes before and after optimization,not only the total delivery time,penalty cost of time window,driving distance and average vehicle rate are reduced,but also the number of vehicles has decreased by one.Next,this paper uses the genetic tabu search algorithm to optimize the model.The total delivery time,penalty cost of time window,and driving distance are further reduced before and after optimization.The validity of the hybrid algorithm is verified by an example analysis,which provides a guidance for enterprises to improve material distribution efficiency and economic benefits.