An evolutionary algorithm for 2D semi-guillotinable circular saw cutting

We define a new class of 2D-stock cutting problems, the so called semi-quillotinable problems, and show its practical importance in solving the task of creating optimal cutting plans for a circular saw. Furthermore, we create a new algorithm suited for solving of semi-guillotinable problems by adapting existing evolutionary algorithms for both guillotinable and non-guillotinable 2D stock cutting problems. This algorithm is compared to standard algorithms on a selected set of both benchmark and real-life problems.