TWO-DIMENSIONAL GUILLOTINE RECTANGULAR STOCK CUTTING OPTIMIZATION WITH PREDETERMINED IN-DEPTH SEARCH STEPS

Stock cutting problem is a kind of general resource allocation problem where the objective is to subdivide a given quantum of a resource into a number of predetermined allocations so that the left- over amount is minimized. In this paper, a new algorithm for the two-dimensional guillotine rectangular stock cutting optimization (GRSCO) is proposed. Experiment results show that it can be widely applied to many related stock cutting fields because of its high efficiency and flexibility.