Research On Crude Oil Selection Optimization Based On Multi-objective Grasshopper Algorithm And Its Supply Chain Network

Energy is very important in the economy and society.Without energy,the whole society has no power.Energy has an uneven distribution of regions.And logistics is the effective transfer of goods from the place of origin to the place of consumption.Energy and logistics,as both industries,play an important role in the country's economic and social development.Among them,energy is an important material foundation,logistics can make products realize value,and they are interdependent and promote development each other.Petroleum and petrochemical industry logistics,as a kind of energy logistics,has important reference significance for its own development on the study of its own characteristics and the perspective of logistics.Crude oil is one of the most important energy sources in the development of society today.However,the growth of China's crude oil output is lower than the demand growth,which may make the gap in China 's crude oil supply continue to expand.In the absence of raw materials,in order to ensure the stability of supply,this article intends to proceed from two aspects.On the one hand,when a certain crude oil supply is interrupted or insufficient,crude oil blending technology is used to find alternative crude oil.On the other hand,from the perspective of the supply chain,the supply chain network of crude oil is evaluated,and the current situation of the crude oil supply chain is reflected through the evaluation system,which can provide suggestions for policy formulation to meet demand in the future.The main research work of this paper is as follows:(1)An improved multi-objective grasshopper optimization algorithm is proposed and applied to the problem of crude oil selection and hybrid optimization.In the selection of crude oil,this paper considers the minimum deviation between the properties of the crude oil and the target crude oil according to the properties of the crude oil.At the same time,it considers the minimum raw material cost of the mixed crude oil to construct a multi-objective model about crude oil selection,and proposes an improved algorithm,which is named IMOGOA and has better solution effect than NSGA-II algorithm.Then,we select a set of actual real crude oil data,apply new improved algorithm and solve this multi-objective problem through matlab simulation to obtain a set of crude oil mixing schemes.In order to better apply the algorithm to solve and save the time and cost of manual calculation,this paper develops a set of Web-based software about the optimization of crude oil selection.It mainly uses front-end technology Angular JavaScript and Bootstrap,and back-end C#technology for development.This has a great reference role for the informatization and intelligence of the petrochemical industry.The software is valuable in practical application widely.(2)The model of crude oil market demand is constructed and a new evaluation index system of crude oil supply chain network is proposed.We establish a model of market demand in accordance with market rules and determine a model through simulation.The forecast error rate is controlled within 3%.It can be seen from the demand model that future demand is growing.From the original petroleum product orientation to demand orientation,then we analysis various factors in the supply chain of crude oil to establish a supply chain evaluation system of the crude oil,which reflects the current situation of the supply chain of crude oil,and it can guide the reverse traction of procurement and transportation when demand changes,and provide a basis for the formulation and implementation of future policies of the crude oil.