Scheduling Optimization Of Route-Loading Combined Logistics Under Uncertain Demand Environment

As a composite service industry,the logistics industry integrates multiple industries such as transportation,storage and information,and is an extremely important component of the national economy.At present,my country is a big logistics country,but it is far from a strong logistics country.The most important constraint is that logistics costs remain high.Reducing logistics costs has become a key issue that the logistics industry needs to solve urgently.However,transportation cost,management cost and storage cost are the three important components of logistics cost.Among them,transportation cost accounts for a large proportion of logistics cost.Therefore,optimizing the transportation process,reducing transportation costs,and improving logistics transportation efficiency are of great significance for reducing overall logistics costs and improving logistics quality.The problem of vehicle path optimization is the core problem in the logistics field.It reduces the transportation cost of vehicles by optimizing the driving path of the vehicle on the premise of meeting the needs of different customers.However,in the actual logistics and transportation process,not only the travel path of the vehicle needs to be considered,but also the loading problem of the vehicle compartment.For example,for van transport vehicles,the internal loading space is limited.How to optimize the types of containers loaded in the compartments and the number will directly affect the loading rate of vehicles and indirectly affect the number of vehicles dispatched.These factors will restrict transportation costs.At the same time,in the actual production process of the enterprise,due to the limitation of production factors,the enterprise is often uncertain about the demand for various types of goods needed in the future.In this case,the transportation vehicles dispatched by the decision makers are in various supplies.The point-to-cycle pick-up process will cause serious vehicle waste,low carriage loading rate,and vehicle detours.All of these make reasonable optimization of the transportation process an important issue facing enterprises in production logistics.Therefore,in an uncertain demand environment,this research conducted a research on the collaborative optimization problem of multi-vehicle travel paths and carriage loading of multiple types of goods for the circular pickup problem,and proposed a combined logistics scheduling based on VRP and 3D-KLP optimize the model,and design a multi-stage algorithm to solve the model.The main work of this research is as follows:Firstly,the hybrid particle swarm optimization algorithm based on genetic algorithm and heuristic orthogonal binary tree search algorithm were used to solve the optimal driving path of different vehicle types and the optimal quantity of various types of goods loaded in the compartment,and then the optimal routing-loading scheme of each vehicle type was determined.Then,taking these schemes as decision variables and the actual cargo demand as constraint conditions,a new routing-loading collaborative optimization model based on actual demand was established and solved,and the number of vehicles executed according to the optimal scheme of different vehicle types was obtained.Finally,through the optimization and foreign scholars in recent authoritative periodicals result comparison and practical application from two aspects of the case study and verification,to prove the feasibility and validity of this research method,and thus established a in different models bike "routing + loading" compound solution for decision making units,based on the requirement of the actual constraints.Then a new method of logistics vehicle scheduling is proposed to solve the problem of uncertain demand with optimal combined solutions.