Title :
Solving integrative matching model of inventory in continuous casting and hot rolling processes by improved genetic algorithm
Author :
Li, Haitao ; Li, Sujian ; Wu, Di
Author_Institution :
Sch. of Mech. Eng., Univ. of Sci. & Technol., Beijing, China
Abstract :
To solve the problem of matching slabs and coils against orders in the process of hot rolling production in steel industry, we introduce matrices in which the element indicates difference between slab material and steel required in order, and also matrices in which the element indicates difference between coil and steel required in order. A multi-objective 0-1 programming model is established. And then, an improved genetic algorithm with sub-integer encoding method and heuristic repair strategy is proposed. Finally, effectiveness of the model and algorithm is verified by simulation based on actual production data. Simulation experiments show that the proposed method could gain more scientific and reasonable matching results.
Keywords :
casting; coils; encoding; genetic algorithms; hot rolling; integer programming; inventory management; maintenance engineering; slabs; steel; steel industry; coil; continuous casting; heuristic repair strategy; hot rolling production process; improved genetic algorithm; integrative matching model solving; inventory; matching problem; matrices; multiobjective 0-1 programming model; production data; slab material; steel; steel industry; subinteger encoding method; Coils; Genetic algorithms; Materials; Mathematical model; Slabs; Steel; Orders; continuous casting and hot rolling; improved genetic algorithm; integrative matching; inventory;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2012 10th World Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-1397-1
DOI :
10.1109/WCICA.2012.6359450
