Edinburgh Napier University

  The cutting stock problem it is of great interest in relation with several real world problems. Basically it means that there are some smaller pieces that have to be cut from a greater stock piece, in such a way, that the remaining part of the stock piece should be minimal. The classical solution methods of this problem generally need a great amount of calculation. In order to reduce the computational load they use heuristics. A newer solution method is presented in this paper, which is based on a genetic technique. This method uses a tree representation of the cutting pattern, and combines different patterns in order to achive patterns with higher performance. The combination of the cutting patterns is realized by a combined crossover-mutation operator. An application of the proposed method is presented briefly in the end of the paper.