Cutting stock waste reduction using genetic algorithms

Y. Khalifa, O. Salem, A. Shahin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Scopus citations

Abstract

A new model for the One-dimensional Cutting Stock problem using Genetic Algorithms (GA) is developed to optimize construction steel bars waste. One-dimensional construction stocks (i.e., steel rebars, steel sections, dimensional lumber, etc.) are one of the major contributors to the construction waste stream. Construction wastes account for a significant portion of municipal waste stream. Cutting one-dimensional stocks to suit needed project lengths results in trim losses, which are the main causes of one-dimensional stock wastes. The model developed and the results obtained were compared with real life case studies from local steel workshops. Cutting schedules produced by our new GA model were tested in the shop against the current cutting schedules. The comparisons show the superiority of this new GA model in terms of waste minimization.

Original languageEnglish (US)
Title of host publicationGECCO 2006 - Genetic and Evolutionary Computation Conference
PublisherAssociation for Computing Machinery (ACM)
Pages1675-1680
Number of pages6
ISBN (Print)1595931864, 9781595931863
DOIs
StatePublished - 2006
Event8th Annual Genetic and Evolutionary Computation Conference 2006 - Seattle, WA, United States
Duration: Jul 8 2006Jul 12 2006

Publication series

NameGECCO 2006 - Genetic and Evolutionary Computation Conference
Volume2

Other

Other8th Annual Genetic and Evolutionary Computation Conference 2006
CountryUnited States
CitySeattle, WA
Period7/8/067/12/06

Keywords

  • Cutting Stock Problem
  • Genetic Algorithms
  • Waste Reduction

ASJC Scopus subject areas

  • Engineering(all)

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