Combinatorial optimization method of steel coil stacking of hood-type annealing furnace

Abstract

The invention relates to the technical field of ferrous metallurgy information technology, and particularly relates to a combinatorial optimization method of steel coil stacking of a hood-type annealing furnace. According to the characteristics of an annealing process of a hood-type annealing furnace, based on the analysis of the effect of steel coil overall dimensions (external diameter, width, thickness, etc.) and steel grades on annealing time and the restriction of various constraint conditions, and aiming at the optimization objects of minimizing stacking number and maximizing furnace stage production efficiency, the invention establishes a mathematical model for the optimization of hood-type furnace stacking, and provides a hybrid genetic algorithm (FGSA) combining algorithms of a first fit decreasing algorithm (FFD), a genetic algorithm (GA), and a simulated annealing algorithm (SA) for the solution of the model. The method can realize the informatization and the automation of hood-type furnace annealing production, reduce the labor intensity of scheduling personnel, increase the production efficiency of production factories, and has the effect of energy saving and consumption reduction.

Description

technical field [0001] The invention relates to the technical field of iron and steel metallurgy information technology, in particular to a method for optimizing the stacking combination of steel coils in a bell annealing furnace. Background technique [0002] In the past, the steel coil stacking group furnace plan of the bell annealing furnace was completely compiled manually based on personal experience, while the production mode of the bell annealing furnace has the characteristics of long cycle, high energy consumption, complicated operation steps, many constraints, and high randomness. Therefore, the preparation of plans has become a cumbersome work requiring high production experience, and manual preparation of plans often cannot take into account the requirements of annealing quality, production capacity and production efficiency at the same time. Therefore, it is necessary to find an optimization algorithm combined with software and automation technology to realize t...

AI Technical Summary

Problems solved by technology

The branch and bound method is highly skilled. If the weights of each node are not properly selected and the branch boundaries are not estimated well, the efficiency of the algorithm will be greatly affected. In extreme cases, it will not be much different from exhaustive search; the adaptability of the expert system is poor , relying on the accumulation of empirical knowledge, it is not suitable for uncertain production environments; the simple genetic algorithm or ant colony algorithm have the disadvantages of prematurely falling into local extremum and slow search speed

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