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Clarifying Cutting and Sewing Processes with Due Windows Using an Effective Ant Colony Optimization

机译：使用有效的蚁群优化方法，通过适当的窗口来澄清切割和缝纫过程

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摘要

The cutting and sewing process is a traditional flow shop scheduling problem in the real world. This two-stage flexible flow shop is often commonly associated with manufacturing in the fashion and textiles industry. Many investigations have demonstrated that the ant colony optimization (ACO) algorithm is effective and efficient for solving scheduling problems. This work applies a novel effective ant colony optimization (EACO) algorithm to solve two-stage flexible flow shop scheduling problems and thereby minimize earliness, tardiness, and makespan. Computational results reveal that for both small and large problems, EACO is more effective and robust than both the particle swarm optimization (PSO) algorithm and the ACO algorithm. Importantly, this work demonstrates that EACO can solve complex scheduling problems in an acceptable period of time.
机译：裁剪和缝纫过程是现实世界中传统的流水车间调度问题。这种两阶段的柔性流水车间通常与时装和纺织工业中的制造相关。许多研究表明，蚁群优化（ACO）算法对于解决调度问题是有效的。这项工作应用了一种新颖的有效蚁群优化（EACO）算法来解决两阶段灵活的流水车间调度问题，从而最大程度地减少了早期，拖延和制造期。计算结果表明，对于小问题和大问题，EACO均比粒子群优化（PSO）算法和ACO算法更有效，更健壮。重要的是，这项工作证明了EACO可以在可接受的时间内解决复杂的计划问题。

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  • 来源
    《Mathematical Problems in Engineering》 |2013年第3期|182598.1-182598.12|共12页
  • 作者

    Rong-Hwa Huang; Shun-Chi Yu;

  • 作者单位

    Department of Business Administration, Fu Jen Catholic University, New Taipei City, Taiwan;

    Graduate School of Business Administration, Fu Jen Catholic University, New Taipei City, Taiwan;

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