Research on the application of genetic algorithm for the panel cutting stock

Cutting stock is concerned with how to saving material, optimize resources in product designing, manufacturing. It is very complicated and difficult in computing theory, but it has got the extensive application in the actual manufacture. In this paper, genetic algorithm optimization of two-dimensional sheet metal nesting design, genetic algorithm is a numerical method for global optimization. Compared with traditional optimization algorithms, the advantage is a function not asks for much; generally do not fall into local optimal solution, more suitable for solving large scale discrete optimization problems. This genetic algorithm is applied to engineering problems of a typical discrete optimization problem - large scale rectangular parts layout, by the algorithm can find the layout efficient processing methods.