A Study On The Joint Optimization Problem Of Multi-part Three-dimensional Packing And Recycling Pickup Path

According to relevant statistics,my country’s social logistics costs have always been at a relatively high level,and transportation costs account for more than half of them.In this context,the application of the third-party logistics model is gradually popularized.More and more suppliers and manufacturers tend to choose professional third-party logistics companies or spontaneously organize to form a logistics model of circular pickup.How to effectively improve vehicle loading Rates and reducing the cost of vehicle transportation have received widespread attention.This article considers the actual situation of the supply distribution center with multiple parts recycling and unloading to the distribution center as a reserve material.The constraints of immovability and last-in-first-out of the loaded goods are appropriately relaxed,and the goods are loaded first in the transportation process.Replace the position with the after-loading cargo to improve the utilization of the compartment space;at the same time,the cargo of the same node is allowed to be split and transported to increase the way of cargo combination,thereby establishing a multi-purpose vehicle with the least number of vehicles,the shortest travel path,and the least number of cargo movements.Joint optimization problem model for parts three-dimensional packing and cyclic pick-up path.This paper uses a heuristic algorithm to solve the model.Under the condition of relaxing the constraints of LIFO and the inseparability of goods from the same supplier,first use an improved genetic algorithm to solve the optimal multi-part cyclic pick-up under the constraints of the entire vehicle.Path problem;then on the basis of the obtained path plan,use the composite block packing algorithm to solve the three-dimensional packing plan of each vehicle;finally,by comparing the routing plan and the supplier ranking in the packing plan,the number of goods movement is minimized Processing,get the final complete transportation plan.International standard examples and random examples are used to verify the scientificity of the model and the effectiveness of the algorithm.In the calculation results of the standard calculation example,on average,only one cargo is moved by each vehicle,and it only moves0.8 times,but the total path distance is reduced by 3.63% compared with the optimization results of the existing literature;while in the random calculation In the calculation result of the example,whether the loaded goods can be moved and last in first out and whether the goods of the same node can be split and transported are used as variables,and the optimization results are compared.When the constraints are appropriately relaxed,the number of vehicles used is reduced from 6 to 5,and the path is The total distance is reduced by 5.03%.The model and algorithm are scientific and effective.