Minimizing cutting wastes of reinforcement steel bars using genetic algorithms and integer programming models

O. Salem, A. Shahin, Y. Khalifa

Research output: Contribution to journalArticlepeer-review

38 Scopus citations


Materials that are in the form of one-dimensional stocks such as steel rebars, structural steel sections, and dimensional lumber generate a major fraction of the generated construction waste. Cutting one-dimensional stocks to suit the construction project requirements result in trim or cutting losses, which is the major cause of the one-dimensional construction waste. The optimization problem of minimizing the trim losses is known as the cutting stock problem (CSP). In this paper, three approaches for solving the one-dimensional cutting stock problem are presented. A genetic algorithm (GA) model, a linear programming (LP) model, and an integer programming (IP) model were developed to solve the one-dimensional CSP. Three real life case studies from a steel workshop have been studied. The generated cutting schedules using the GA, LP, and IP approaches are presented and compared to the actual workshop's cutting schedules. The comparison shows a high potential of savings that could be achieved using such techniques. Additionally, a user friendly Visual Basic computer program that utilizes genetic algorithms for solving the one-dimensional CSP is presented.

Original languageEnglish (US)
Pages (from-to)982-992
Number of pages11
JournalJournal of Construction Engineering and Management
Issue number12
StatePublished - 2007


  • Algorithms
  • Bars
  • Construction management
  • Optimization
  • Steel
  • Structure reinforcement

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction
  • Industrial relations
  • Strategy and Management


Dive into the research topics of 'Minimizing cutting wastes of reinforcement steel bars using genetic algorithms and integer programming models'. Together they form a unique fingerprint.

Cite this