Optimization Of The Secondary Distribution Path Of Refined Oil Products With Multiple Vehicle Types And Multiple Oil Products Under Random Demand

With the rapid development of the national economy,the demand for oil is still on the rise.However,due to the late start of China’s refined oil sales companies and the influx of more mature oil sales companies from abroad,China’s domestic refined oil sales companies are facing huge challenges.Threats to reduce distribution costs have become a concern for oil product sales companies.However,at present,most domestic oil product sales companies use manual experience to formulate distribution plans,which are often not scientific and reasonable,which also brings higher costs.In this regard,this article studies the optimization of the secondary distribution path of refined oil products with multiple models and multiple oil products under random demand,and uses literature research,mathematical modeling,simulation and other methods to conduct in-depth research on the secondary distribution path of refined oil products.The main research contents are as follows:Firstly,the research background,research purpose and significance of this article are put forward,and related researches of domestic and foreign scholars in recent years are summarized and reviewed.Finally,the main research contents of this article are proposed.Then,the inventory-routing problem of the secondary distribution of refined oil products based on a single vehicle model and a single oil product is studied.A mathematical model is constructed with the target of total distribution cost,which takes into account constraints such as full load,full unloading,and time window.The distribution level of refined oil sales is used to obtain the demand and service time window of each gas station.The genetic algorithm designed in this article is used to solve the calculation example,which verifies the feasibility of the algorithm.Then,the constraints of multiple models were added.The problem of secondary distribution inventory of product oil under random demand was studied.The service level was used to determine the demand for gas stations.The multiple models were constructed under the constraints of full load and unloading,multiple models,and time windows.A mathematical model for the vehicle routing problem of secondary distribution of multi-product refined oil products,and then on the designed single vehicle genetic algorithm,the algorithm can solve the routing problem of secondary distribution vehicles of multi-model multi-product refined oil products by improving the cross rules,and It is found from the results of the example that the improved genetic algorithm is due to the unimproved genetic algorithm in both iteration speed and cost.Finally,taking A product oil sales company as a specific case,combined with the algorithm designed in the article,a better solution than manual formulation was obtained in a short time,further verifying the feasibility of the algorithm,and also showing that the algorithm can be a product oil.Sales companies provide guidance and solve practical problems.