In this paper, we study the cutting stock problem with usable leftovers (CSPUL), that consists in determining a policy of usable leftovers from cut objects. These leftovers, if large enough, can returned to the stock as retails in order to fulfill future demands and, therefore, they are not computed as waste. In order to solve the CSPUL, several heuristic procedures from the literature can be used. However, it is hard to point out which solution method performs better, since each one presents different solutions regarding some conflicting characteristics, such as quantity of new retails generated, wastes, and distribution of the wastes and retails in the cut objects. To overcome this difficulty, we propose some fuzzy techniques to consider the contribution of each characteristic in the solution, classify it according some criteria beforehand considered and, finally, identify the best solution method based on the respective solution. With the proposed fuzzy methodology, the solution methods analysis was simplified
cutting stock problems; usable leftovers; fuzzy inference
