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Minimizing Cutting Wastes of Reinforcement Steel Bars Using Genetic Algorithms and Integer Programming Models.
- Source :
-
Journal of Construction Engineering & Management . Dec2007, Vol. 133 Issue 12, p982-992. 11p. 2 Black and White Photographs, 4 Diagrams, 9 Charts, 2 Graphs. - Publication Year :
- 2007
-
Abstract
- 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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 07339364
- Volume :
- 133
- Issue :
- 12
- Database :
- Academic Search Index
- Journal :
- Journal of Construction Engineering & Management
- Publication Type :
- Academic Journal
- Accession number :
- 27501133
- Full Text :
- https://doi.org/10.1061/(ASCE)0733-9364(2007)133:12(982)