A study on decision making of cutting stock with frustum of cone bars

Lin Liu (), Xinbao Liu, Jun Pei, Wenjuan Fan and Panos M. Pardalos
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Lin Liu: Hefei University of Technology
Xinbao Liu: Hefei University of Technology
Jun Pei: Hefei University of Technology
Wenjuan Fan: Hefei University of Technology
Panos M. Pardalos: University of Florida

Operational Research, 2017, vol. 17, issue 1, No 9, 187-204

Abstract: Abstract 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.

Keywords: Cutting stock; Multi-objective optimization; Multi-attribute decision making; Frustum of cone bars (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s12351-015-0221-x

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