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Minimising earliness and tardiness by integrating production scheduling with shipping information

机译:通过将生产计划与运输信息相集成,最大程度地减少提早和拖延

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摘要

Minimisation of earliness and tardiness is known to be critical to manufacturing companies because it may induce numerous tangible and intangible problems, i.e. extra storage cost, spacing, risk of damages, penalty, etc. In literature, earliness and tardiness is usually determined based on order due date, generally regarded as the time of delivering the finished products to the customers. In many papers, delivery time and cost required are usually simplified during the production scheduling. They usually assume that transportation is always available and unlimited. However, transportation usually constructs a critical portion of the total lead time and total cost in practice. Ignoring that will lead to an unreliable schedule. This is especially significant for electronic household appliances manufacturing companies as the studied company in this paper. In general, they usually rely on sea-freight transportation because of the economic reasons. As different sea-freight forwarders have different shipments to the same destination but with different shipping lead time, cost and available time. Adequately considering this shipping information with the production scheduling as an integrated model can minimise the costs induced by earliness and tardiness and the reliability of the schedule planned. In this paper, a two-level genetic algorithm (TLGA) is proposed, which is capable of simultaneously determining production schedule with shipping information. The optimisation reliability of the proposed TLGA is tested by comparing with a simple genetic algorithm. The results indicated that the proposed TLGA can obtain a better solution with lesser number of evolutions. In addition, a number of numerical experiments are carried out. The results demonstrate that the proposed integrated approach can reduce the tardiness, the storage cost, and shipping cost.
机译:众所周知,尽早和拖延程度的最小化对于制造公司而言至关重要,因为它可能会引发许多有形和无形的问题,例如额外的存储成本,间隔,损坏风险,罚款等。在文献中,通常根据订单来确定是否早于拖延截止日期,通常视为将成品交付给客户的时间。在许多论文中,通常在生产计划过程中简化了交货时间和所需的成本。他们通常认为运输始终可用且不受限制。但是,在实践中,运输通常占总交付时间和总成本的关键部分。忽略这一点将导致时间表不可靠。对于本文研究的电子家用电器制造公司而言,这尤其重要。通常,由于经济原因,它们通常依靠海运。由于不同的货运代理人到同一目的地的货运量不同,但交货时间,成本和可用时间不同。将此运输信息与生产计划表作为一个集成模型充分考虑,可以最大程度地减少因过早和拖延而引起的成本以及计划表的可靠性。本文提出了一种两级遗传算法(TLGA),该算法能够同时确定带有运输信息的生产计划。通过与简单遗传算法比较,测试了所提出的TLGA的优化可靠性。结果表明,提出的TLGA可以以较少的进化次数获得更好的解决方案。另外,进行了许多数值实验。结果表明,所提出的集成方法可以减少拖延,存储成本和运输成本。

著录项

  • 来源
    《International Journal of Production Research》 |2013年第8期|2253-2267|共15页
  • 作者单位

    Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Horn, Hong Kong;

    Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Horn, Hong Kong;

    Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Horn, Hong Kong;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    production planning; due date scheduling; distribution; genetic algorithm;

    机译:计划生产;到期日安排;分配;遗传算法;
  • 入库时间 2022-08-17 13:37:13

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