A hierarchical approach for one-dimensional cutting stock problems in the steel industry that maximizes yield and minimizes overgrading

• Published in: European journal of operational research Vol. 114; no. 1; pp. 72 - 82
• Main Authors: Vasko, Francis J, Newhart, Dennis D, Stott, Jr, Kenneth L
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01-04-1999; Elsevier; Elsevier Sequoia S.A
• Series: European Journal of Operational Research
• Subjects: Algorithms; Applied sciences; Cutting stock; Cutting tools; Exact sciences and technology; Flows in networks. Combinatorial problems; Heuristic; Heuristics; Hierarchies; Mathematical models; Metals application; Operational research and scientific management; Operational research. Management science; Operations research; Production management; Steel industry; Steel products; Studies; United States > US; Cutting stock; Heuristics; Metals application; Mathematical formula; Metal; Combinatorial problem; Cutting stock problem; Mathematical programming
• ISSN: 0377-2217; 1872-6860
• DOI: 10.1016/S0377-2217(98)00035-6

In the steel industry, as hot steel products exit the producing facility, they are cut at primary saws (hotsaws) into shorter pieces. After these pieces cool, they are inspected for defects and either applied directly to customer orders or are further cut to ordered lengths at secondary saws (cold saws). In this case study, we will describe a hierarchical algorithm, DYNACUT_CS, that efficiently and effectively generates cutting patterns for material that is to be cut at cold saws. DYNACUT_CS strives to maximize yield over all the material cut and simultaneously tries to minimize overgrading (applying higher quality material than specified by the customer). An example will be given to illustrate how the algorithm works. This approach has been implemented for a variety of products at several different Bethlehem Steel Corporation facilities.