Optimization Analysis Of Steel Cost Based On Sensitivity Analysis And Genetic Algorithm

As an important industrial fundamental material,steel has many properties related to some important areas such as politics,commodity and finance.It is of great significance to analyze and optimize the cost of steel and conduct better cost control accordingly for enhancing the profitability of enterprises and enhancing the competitiveness of enterprises in the market.In this paper,price data of rebar steel is selected as the research object,and 8 important factors affecting its cost are screened through sensitivity analysis.For the factors with higher sensitivity,Matlab genetic algorithm is applied to optimize,and the optimized cost scheme is obtained,which is summarized as follows:Firstly,through Sobol global sensitivity analysis method of influencing factors of rebar costs time series analysis,get four significant factors,respectively: 62% Australian fine ores forward spot prices 1,My Cpic coke absolute price index 2,domestic foundry pig iron absolute price index(comprehensive)5 and billet absolute prices index(comprehensive)6,and on the above four sensitivity coefficient is higher in turn do local sensitivity analysis of parameters,the sensitive degree of various parameters on the cost of rebar.Among them,the absolute price index of billet(comprehensive)6 has the highest sensitivity value,which is 0.9467,the absolute price index of My Cpic coke 2 and the absolute price index of cast pig iron(comprehensive)5 are 0.8815,0.8228 and 62%,respectively.The forward spot price of Australian ore 1 is not much different from the other three factors,which is 0.7668.Secondly,based on the results of sensitivity analysis,this paper establishes a cost optimization model for rebar steel,selects sensitive factors as design variables,and uses the cost of rebar steel and the increase range of sensitive factors as constraints to optimize the model with genetic algorithm.Results show that under the interaction of multiple factors,when 62% Australian fine ores forward spot prices 1 absolute price index fall 15%,My Cpic coke 2 absolute price index rise 12%,domestic foundry pig iron absolute price index(comprehensive)5 reduce by 28%,billet absolute price index(comprehensive)reduced by 5%,rebar costs is closed to optimal state,with a drop of 25%.It shows that the optimization algorithm is effective.According to the results of model optimization,this paper puts forward some suggestions,such as rational use of raw material futures market,flexible adjustment of purchasing plan and so on,providing new ideas for enterprise production strategies.