Research On The Production Scheduling Of Scrap Iron And Steel Remanufacturing In Low Carbon Environment

Scrap iron and steel is a recyclable renewable resource,which has significant resources and low carbon advantages compared to iron ore raw materials.Under the background of national energy saving and emission reduction,actively promoting scrap steel remanufacturing is an important way for the steel industry to achieve low-carbon development,and it is also the main direction of China’s steel industry development.China launched the carbon emissions trading market at the end of December 2017,ranking the steel industry as one of the eight most important emissions industries.This initiative has become a powerful “pushing hand” to accelerate energy conservation and emission reduction in the steel industry.Carbon emission reduction measures will eventually be implemented in specific production links,and carbon emissions have become one of the key factors that enterprises have to consider when formulating production scheduling schemes.Therefore,it has a very important theoretical and practical value to study scientifically making a production scheduling schemes for scrap iron and steel remanufacturing in a low-carbon environment.The main task is to achieve effective coordination between core production processes and highly coordinated operation between subsystems,reduce carbon dioxide emissions from the production scheduling level,and promote the green cycle development of the steel industry.This paper studies the production scheduling optimization problems of scrap iron and steel remanufacturing system considering both economic and environmental benefits in a low-carbon environment,based on the key production links of energy consumption and carbon emission in the reprocessing subsystem and remelting subsystem.Main research contents are as follows:(1)For the whole production process of scrap iron and steel reprocessing and electric arc furnace charging,considering the factors of process constraints and material balance,the carbon emission measurement method is designed,and a low carbon scheduling optimization model that minimized the sum of economic cost and carbon transaction cost is established.By comparing with the model considering only economic cost,the feasibility and effectiveness of the model in carbon emission reduction are theoretically demonstrated.Further,the effects of carbon cap,carbon price and carbon trade on total cost,carbon emissions and optimal scheduling schemes are analyzed by some numerical examples.The study achieve a highly coordinated operation between the scrap iron and steel reprocessing subsystem and the remelting subsystem,which reduce material losses and carbon emissions jointly.(2)For the production process of scrap steelmaking and mould casting,a carbon emission measurement method is designed,and a dual-objective optimization model is established with the objectives to minimize the makespan and carbon emissions.Aiming at the characteristic that the model has limited waiting time,a population-based increased learning algorithm using probability update mechanism is proposed.The algorithm extends the standard 2-dimensional probability matrix to a3-dimensional matrix according to the working procedure request of scrap steelmaking and mould casting,establishes a new update mechanism,and uses the probability model to generate each generation of population.Because of the probability selection operation on the gene position of the solution,the algorithm can quickly and efficiently learn the arrangement information of the high-quality solution,so that the high-quality scheduling scheme can be obtained in a short time.Finally,we analyze the main factors affecting carbon emissions,and the relationship between makepan and carbon emissions.This study provides an effective method for enterprises to select optimal production scheduling schemes with comprehensive objectives based on production tasks and carbon emission environment.(3)For the production process of scrap steelmaking and continuous casting with identical technological route,the carbon emission measurement method is designed.Considering the process constraints,a dual-objective optimization model is established to minimize the makespan and carbon emissions simultaneously.Aiming at the strong constraint characteristics of the model,such as limited residence time of the charge,batch production in the continuous casting stage and on-time casting,an improved population-based increased learning algorithm is proposed.The algorithm uses an improved probability model to generate each generation of population,and performs a more efficient global search on solution space of the problem.The local search algorithm integrated with time window backward moving scheme is designed to optimize dual objectives simultaneously.Since the good balance between global search and local search,the algorithm has the ability to obtain good solutions.Simulation results indicate that,compared with the scheduling results of the model that only consider the optimization of economic indicators,the optimization model can effectively reduce carbon emissions while optimizing economic indicators.In addition,the scheduling schemes meet the upper limit of the residence time,thus effectively reducing the carbon emissions caused by the rescheduling risk.(4)For the production process of scrap steelmaking and continuous casting with complicated technological route,the carbon emission measurement method is designed.A multi-objective optimization model is established with the objectives to minimize the makespan,carbon emissions and maximum waiting time of the charge.For the issue of many types of objectives and contradictions among objectives in the model,a non-dominated sorting genetic algorithm is proposed.Individual evaluation of fast non-dominated sorting and diversity maintenance strategy based on crowded distance make the algorithm achieve better solution effect.Simulation results indicate that,this model and its solution can not only provide compromise schedule that balance various objectives for the scheduling decision makers,but also provide a satisfactory scheduling scheme under different carbon emission policies.This study can help improve the relevant research theories and methods of scrap iron and steel remanufacturing,and it has important practical significance to help scrap iron and steel remanufacturing enterprises to make reasonable production scheduling schemes in a low-carbon environment.