A NEW HEURISTIC ALGORITHM FOR TWO-DIMENSIONAL DEFECTIVE STOCK GUILLOTINE CUTTING STOCK PROBLEM WITH MULTIPLE STOCK SIZES

This paper mainly addresses a two-dimensional defective stocks guillotine cutting stock problem where stock of different sizes is available. Herein a new heuristic algorithm which is based on tree is proposed to discuss this problem. In particular, such an algorithm consists of two parts: the first part is an initial solution of the cutting stock problem where there are no defects on the stocks; the second part is the final optimization solution which is set up on the basis of the first part and takes the defects into consideration. This paper also evaluates the performance of the proposed algorithm. The experimental results demonstrate the effectiveness of the algorithm for the two-dimensional defective stocks cutting stock problem and show that the algorithm can improve not only the utilization rate of stocks, but also the reuse rate of remainders by reducing the fragmentation of remainders.