Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Three-step solutions for cutting stock problem of construction steel bars
Abstract The cutting stock problem of construction steel bars has a strongly heterogeneous assortment of demand items. This research develops new solution procedures which result in the efficient cutting plans with minimum trim loss and number of stocks used. The procedures consist of three steps namely the generation of a set of efficient cutting patterns, the optimization of one dimensional cutting stock problem, and the cut of undersupplied items with the best fit decreasing algorithm. The first step, the Intensive Search algorithm generates a set of efficient cutting patterns which are made up of various demand lengths according to their demands quantities. The second step, the optimization of One Dimensional Cutting Stock Problem (1D-CSP) using Genetic Algorithm is proceeded to determine the numbers of cutting times of the patterns. All these cut items are constrained to not exceed the demanded pieces. The third step, few remaining undersupplied items are cut using the best fit decreasing algorithm. Test results showed that the solutions from different runtimes gave comparable percentages of waste. Important parameters such as the number of efficient cutting patterns and the allowable trim loss of the patterns could affect the solutions. Test results indicated that the new solution procedures could give low-waste cutting plans.
Three-step solutions for cutting stock problem of construction steel bars
Abstract The cutting stock problem of construction steel bars has a strongly heterogeneous assortment of demand items. This research develops new solution procedures which result in the efficient cutting plans with minimum trim loss and number of stocks used. The procedures consist of three steps namely the generation of a set of efficient cutting patterns, the optimization of one dimensional cutting stock problem, and the cut of undersupplied items with the best fit decreasing algorithm. The first step, the Intensive Search algorithm generates a set of efficient cutting patterns which are made up of various demand lengths according to their demands quantities. The second step, the optimization of One Dimensional Cutting Stock Problem (1D-CSP) using Genetic Algorithm is proceeded to determine the numbers of cutting times of the patterns. All these cut items are constrained to not exceed the demanded pieces. The third step, few remaining undersupplied items are cut using the best fit decreasing algorithm. Test results showed that the solutions from different runtimes gave comparable percentages of waste. Important parameters such as the number of efficient cutting patterns and the allowable trim loss of the patterns could affect the solutions. Test results indicated that the new solution procedures could give low-waste cutting plans.
Three-step solutions for cutting stock problem of construction steel bars
Benjaoran, Vacharapoom (Autor:in) / Bhokha, Sdhabhon (Autor:in)
KSCE Journal of Civil Engineering ; 18 ; 1239-1247
20.05.2014
9 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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