Column generation algorithms for mother plate design in steel plants

Qi Zhang, Shixin Liu, Ruiyou Zhang () and Shujin Qin
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Qi Zhang: Northeastern University
Shixin Liu: Northeastern University
Ruiyou Zhang: Northeastern University
Shujin Qin: Northeastern University

OR Spectrum: Quantitative Approaches in Management, 2021, vol. 43, issue 1, No 4, 127-153

Abstract: Abstract This paper investigates the mother plate design (MPD) problem which is a typical problem in the production planning of steel plants. The MPD problem refers to a variant of the two-dimensional variable-sized bin packing problem in which the height of a bin is in a given finite set and the width of each bin is continuous in an interval. The problem is first formulated as a mixed integer nonlinear programming model and then linearized into a mixed integer programming model. We present a column generation-based (CG-based) algorithm to approximately solve the MPD problem, in which a height combination scheme is devised to decrease the dimensions of the pricing sub-problem. We present an accelerated CG (ACG) algorithm with improved performance which adopts two heuristic accelerating strategies in the pricing process. We use practical instances collected from a Chinese steel plant to test the performance of the proposed algorithms. The results indicate that the ACG algorithm is suitable for solving real-world instances.

Keywords: Mother plate design; Two-dimensional variable-sized bin packing problem; Column generation; Accelerated column generation (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s00291-020-00610-z

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