A study on decision making of cutting stock with frustum of cone bars
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This paper considers the cutting stock problem with frustum of cone bars. A multiple objective optimization model is established by taking into account trim loss, the number of cutting patterns and usable leftovers. A decision-making method for solving this cutting stock problem is designed. First, an improved non-dominated sorting heuristic evolutionary algorithm is developed for generating the Pareto non-dominated solutions. Then the weights of the objectives are calculated by combining the subjective methods (subjectively determined by the decision maker) and objective methods (objectively determined by numerical computing). Finally, a multi-attribute decision making method is used for choosing a cutting plan from the Pareto non-dominated solutions. Computational results indicate that the method proposed is feasible.
KeywordsCutting stock Multi-objective optimization Multi-attribute decision making Frustum of cone bars
Supported by the Decision Science and Technology Research Institute, Hefei University of Technology, Hefei, China is gratefully appreciated. This research was supported in part by the National Natural Science Foundation under the Grant Nos.: 71171071, 71231004 and Anhui Universities Natural Science Project under the Grant No.: KJ2011A215.
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