Cutting stock waste reduction using genetic algorithms

  • Authors:

  • Y. Khalifa;O. Salem;A. Shahin

  • Affiliations:

  • State University of New York, New Paltz, NY;The University of Cincinnati, Cincinnati, Ohio;University of Alberta, Edmonton, Alberta, Canada

  • Venue:
  • Proceedings of the 8th annual conference on Genetic and evolutionary computation
  • Year:
  • 2006

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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.