Scholarlink

<p>This paper addresses the Multi-Period Cutting Stock Problem with Due Dates and Setups (MPCSPDDS), an extension of the classical one-dimensional Cutting Stock Problem (CSP). The MPCSPDDS considers the due dates specified in cutting orders’ requests and setups required for transitioning between different cutting patterns. The challenge lies in minimizing tardiness and earliness during production, considering these as detrimental factors. Additionally, the proposed model assumes that a setup is necessary for the cutting machine when switching patterns. The contribution of this paper includes the proposition of an integer mathematical programming model and a matheuristic solution approach for two variants of the MPCSPDDS, employing column generation, a round-up heuristic, and the local branching matheuristic. Computational experiments show that our proposed solution method consistently yields, on average, high-quality feasible solutions compared to employing column generation and solving the problem with the generated columns using the CPLEX solver while maintaining a low computational cost.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A local branching-based solution for the multi-period cutting stock problem with tardiness, earliness, and setup costs

  • 期刊论文

  • 发表日期：

    2025年2月4日

查看全文
  • Elisama de Araújo Silva Oliveira,
  • Elizabeth Wanner,
  • Elisangela Martins de Sá,
  • Sérgio Ricardo de Souza

摘要

This paper addresses the Multi-Period Cutting Stock Problem with Due Dates and Setups (MPCSPDDS), an extension of the classical one-dimensional Cutting Stock Problem (CSP). The MPCSPDDS considers the due dates specified in cutting orders’ requests and setups required for transitioning between different cutting patterns. The challenge lies in minimizing tardiness and earliness during production, considering these as detrimental factors. Additionally, the proposed model assumes that a setup is necessary for the cutting machine when switching patterns. The contribution of this paper includes the proposition of an integer mathematical programming model and a matheuristic solution approach for two variants of the MPCSPDDS, employing column generation, a round-up heuristic, and the local branching matheuristic. Computational experiments show that our proposed solution method consistently yields, on average, high-quality feasible solutions compared to employing column generation and solving the problem with the generated columns using the CPLEX solver while maintaining a low computational cost.