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

fYear

2012

fDate

6-8 July 2012

Firstpage

5133

Lastpage

5138

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation (WCICA), 2012 10th World Congress on

Conference_Location

Beijing

Print_ISBN

978-1-4673-1397-1

Type

conf

DOI

10.1109/WCICA.2012.6359450

Filename

6359450