A residual recombination heuristic for one-dimensional cutting stock problems

B. S. C. Campello (), C. T. L. S. Ghidini (), A. O. C. Ayres () and W. A. Oliveira ()
Additional contact information
B. S. C. Campello: University of Campinas
C. T. L. S. Ghidini: University of Campinas
A. O. C. Ayres: University of Campinas
W. A. Oliveira: University of Campinas

TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, 2022, vol. 30, issue 1, No 9, 194-220

Abstract: Abstract Cutting stock problems arise in manufacturing industries where large objects need to be cut into smaller pieces. The cutting process usually results in a waste of material; thus, mathematical optimization models are used to reduce losses and take economic gains. This paper introduces a new heuristic procedure, called the Residual Recombination Heuristic (RRH), to the one-dimensional cutting stock problem. The well-known column generation technique typically produces relaxed solutions with non-integer entries, which, in this approach, we associate with a set of residual cutting patterns. The central aspect of this contribution involves recombining these residual cutting patterns in different ways; therefore, generating new integer feasible cutting patterns. Experimental studies and statistical analyses were conducted based on different instances from the literature. We analyze heuristic performance by measuring the waste of material, the number of instances solved to optimality, and by comparing it with other heuristics in the literature. The computational time suggests the suitability of the heuristic for solving real-world problems.

Keywords: Cutting stock problem; Multiperiod cutting stock problem; Heuristics; 90C59 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11750-021-00611-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:topjnl:v:30:y:2022:i:1:d:10.1007_s11750-021-00611-3

Ordering information: This journal article can be ordered from
http://link.springer.de/orders.htm

DOI: 10.1007/s11750-021-00611-3

Access Statistics for this article

TOP: An Official Journal of the Spanish Society of Statistics and Operations Research is currently edited by Juan José Salazar González and Gustavo Bergantiños

More articles in TOP: An Official Journal of the Spanish Society of Statistics and Operations Research from Springer, Sociedad de Estadística e Investigación Operativa
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().