Genetic Algorithm for Panel Cutting Stock on CUDA Platform

The problem of placing a number of specific shapes on a raw material in order to maximize material utilization is commonly encountered in the production of steel bars and plates, papers, glasses, etc. In this paper, we presented a genetic algorithm for steel grating nesting design. For application in large-scale discrete optimization problems, we also implemented this algorithm with CUDA based on parallel computation. Experimental results show that under genetic algorithm invoking with CUDA scheme, we can obtain satisfied solutions to steel grating nesting problem with high performance.