Purpose: The purpose has been to demonstrate the possibilities of reducing the cost of steel processing in the BOF Plant by using optimization algorithms in the charge planning.Design/methodology/approach: A lot of production factors and technological relationships impact the BOF processing costs. Practically any change in charge material parameters, like chemistry and temperature of hot metal, scraps and fluxes, as well as market prices of materials and cost of carbon dioxide emission, have to be considered to find an optimum charge mix, which generates the minimum cost and simultaneously complies with all technological and steel quality constraints. A linear optimization task including a simplified version of a BOF static model has been defined and a few examples of typical industry charge planning problem have been solved and presented.Findings: Critical price and amount of a given charge material for current technological conditions, stocks and market situation is the basic information for the Steel Plant management as well as for the Purchase Department. The relationship between material prices, CO2 emission price and material consumption for a given production and logistic constraints have been identified.Research limitations/implications: The paper describes using mathematical optimization methods in a specific area of steel industry, but it is opened problem with large potential of obtaining substantial benefits in other areas.Practical implications: The optimization model has been a base for developing the application for the Steel Plant and Purchase Department to optimize charge mix and plan the charge materials purchasing.Originality/value: The optimization algorithms has been adapted for a specific operation problem in steel making, i.e. calculation of charge for BOF.