Optimization Algorithms And Implementations For Slab Design And Furnace Charge Plan Problem In Iron And Steel Industry

Production schedule problem is one of the most important production managementproblem in steel enterprises, and the slab design and furnace charge plan problemin steelmaking and continuous casting production are the most important parts inproduction scheduling. In recent years, with the accelerating globalization process in ironand steel industry, market competition has become extremely fierce, steel enterprises arefacing increasingly diverse customer requirements, such as multiple varieties and smallbatch. It would definitely leads to inevitable contradictions against large-scale batchproduction, and pose great challenges to production scheduling in steel enterprises. Inorder to reduce the negative effects caused by production contradiction discussed above,the production and management methods must be optimized, so that the matching anddesign between order and slabs must be more effective to meet the need offlexible manufacturing. On the background of production in steel industry, this paperconducted in-depth research on the slab design and furnace charge plan problem.Iron and steel enterprises’ slab design optimization problems include matching andpacking optimization problem. In this paper, knapsack optimization idea is applied toanalyze these problems and set up a multi-objective optimization model to solve thecombination optimization problem. Meeting the production technology constraints andthe combination layout rules, the model is used to meet the optimized target by matchingcontract and slab with minimum waste material, maximum slab design and contractaccomplishment. Clustering and knapsack analysis of the optimization model has beendone. Referring to knapsack problem solving ideas in combination optimizationproblems, the virtual slab and slab designing process are regarded as knapsack andpacking optimization respectively. The idea of designing and solving procedures of thealgorithm are detailed description. Then the paper analyzed the system implementationand application effects. Through the comparative analysis of actual production data, itcan be seen that the algorithm can effectively improve the efficiency and quality of theslab design, which is of great practical value.The furnace charge plan problem in the steelmaking-continuous casting batchproduction scheduling is a multiple knapsack problem based on contract slabs and steelfurnace, belonging to NP-complete problem in the combinatorial optimization. Insteelmaking-continuous casting production, based on slab design results, according to the size of the contract and the steelmaking constriants, the combined virtual slab is batchingmanufactured in furnace, and impacting on the production process of steelmaking androlling according to the different sections of the various types of slabs. This paper built amathematical model for the specifical furnace charge plan problem in large steelenterprise, and designed an IAFSA based on heuristic rules. It can significantly reducethe amount of waste material in steelmaking with a certain feasibility and superiority.This paper developed the software systems for engineering application, whichimplemented intelligent and optimized slab design and furnace charge plan, andimproved the ability of digital control in slab production and manufacturing process. Thispaper also studied the dynamic adjustment technology in production scheduling, andenhanced digitization and informatization in production scheduling and manufacturing toprovide strong support for lean production.