A Mixed-Integer Linear Programming Model for the Cutting Stock Problem in the Steel Industry

Daniel Morillo-Torres, Mauricio Torres Baena, John Wilmer Escobar, Alfonso R. Romero-Conrado, Jairo R. Coronado-Hernández, Gustavo Gatica

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)


A mixed-integer linear programming (MILP) model is proposed for solving a one dimension cutting stock problem (1D-CSP) in the steel industry. A case study of a metallurgical company is presented and the objective is to minimize waste in the cutting process of steel bars, considering inventory constraints and the potential use of the resulting leftovers. The computational results showed that an optimal solution was always found with an average improvement in waste reduction of 80 %. There was no significant difference when comparing results between the complete model and the model without inventory constraints.

Original languageEnglish
Title of host publicationApplied Computer Sciences in Engineering - 8th Workshop on Engineering Applications, WEA 2021, Proceedings
EditorsJuan Carlos Figueroa-García, Yesid Díaz-Gutierrez, Elvis Eduardo Gaona-García, Alvaro David Orjuela-Cañón
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages12
ISBN (Print)9783030867010
Publication statusPublished - 2021
Event8th Workshop on Engineering Applications, WEA 2021 - Virtual, Online
Duration: 6 Oct 20218 Oct 2021

Publication series

NameCommunications in Computer and Information Science
Volume1431 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937


Conference8th Workshop on Engineering Applications, WEA 2021
CityVirtual, Online


  • Cutting stock problem
  • Industrial application
  • Mixed-integer linear programming
  • Steel bars

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics


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