@inproceedings{41dd67a281b7440fb72f8fba28fc9ce6,
title = "Cutting stock waste reduction using genetic algorithms",
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.",
keywords = "Cutting Stock Problem, Genetic Algorithms, Waste Reduction",
author = "Y. Khalifa and O. Salem and A. Shahin",
year = "2006",
doi = "10.1145/1143997.1144272",
language = "English (US)",
isbn = "1595931864",
series = "GECCO 2006 - Genetic and Evolutionary Computation Conference",
publisher = "Association for Computing Machinery (ACM)",
pages = "1675--1680",
booktitle = "GECCO 2006 - Genetic and Evolutionary Computation Conference",
address = "United States",
note = "8th Annual Genetic and Evolutionary Computation Conference 2006 ; Conference date: 08-07-2006 Through 12-07-2006",
}