Minimizing Cutting Wastes of Reinforcement Steel Bars Using Genetic Algorithms and Integer Programming Models |
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Authors: | O. Salem A. Shahin Y. Khalifa |
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Affiliation: | 1Associate Professor, Dept. of Civil and Environmental Engineering, Univ. of Cincinnati, P.O. Box 210071, Cincinnati, OH 45221 (corresponding author). E-mail: osalem@uc.edu 2Graduate Student, Civil and Environmental Engineering Dept., Univ. of Alberta, 220 Civil/Elect. Engineering Bldg., Edmonton AB, Canada T6G 2G7. 3Assistant Professor, Dept. of Electrical and Computer Engineering, State Univ. of New York, Room 202, Resnick Engineering Hall, 75 South Manheim Blvd., New Paltz, NY 12561.
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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. |
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Keywords: | Construction management Algorithms Optimization Structure reinforcement Steel Bars |
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