Research On Optimization Of Steel Bar Preparation In Hydropower Project

At present, very big quantity of reinforcement are used in hydropower project construction, however cutting stock of steel reinforcement still depend on experience mostly, Such situation lead to more waste and more disposal, and engineering cost increase and competition-ability of enterprise weaken. The article is educed from reinforcement cutting stock problem of GuaZhi hydropower project construction, categorization, model foundation and solution of problem of one-dimensional cutting stock are discussed roundly, solution of single standard one-dimensional cutting stock is studied specially in this article, main content are as follow:(1) On basis of foreign and domestic study, aim at defect of study on showing demand and stock accordingly, multi-standard one-dimensional cutting stock model and single-standard one-dimensional cutting stock model are built by using quantitative analysis method, and solution are taken for one-dimensional cutting stock mode, linear programming arithmetic and elicitation arithmetic, genetic algorithm and annealing algorithm. At same time, experiments of reinforcement cutting stock are summarized which create during long time of hydropower project construction qualitatively, which can increase boundary conditions of multi-standard one-dimensional cutting stock largely, and make it more significative to solving problem.(2) In this article, By studying of reinforcement cutting stock problem in hydropower project construction, aiming at reinforcement material with fixed length, solutions are given to solve problem of single- work place or single standard, or a serial number of reinforcement. All problem of reinforcement cutting stock of whole project during construction are solved by splicing of said solutions, by this practice, all-purpose and detail of method of linear-material cutting stock optimization in industrial production are presented, Such outcome are worth of practical using and are helpful generally in future, and will effect engineering costs greatly.