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首页> 外文期刊>International Journal of Production Research >Modelling and solving algorithm for two-stage scheduling of construction component manufacturing with machining and welding process
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Modelling and solving algorithm for two-stage scheduling of construction component manufacturing with machining and welding process

机译：机械加工和焊接过程的建筑构件制造两阶段调度的建模和求解算法

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摘要

This paper focuses on a two-stage machining and welding scheduling problem based on an investigation at a structural metal manufacturing plant, aiming to minimise the total makespan. Several parts processed at Stage one according to classical job-shop scheduling are grouped into a single construction component at the second welding stage. Fabrication of the construction component cannot begin until all comprising parts have been completed at Stage one. This paper establishes a novel mathematic model to minimise the total makespan by mainly considering the dominance relationship between the construction component and the corresponding parts. In order to solve this two-stage problem, we propose an improved harmony search algorithm. A local search method is applied to the best vector at each iteration, so that a more optimal vector can be subsequently realised. The average value, minimum value, relative percentage deviation and standard deviation are discussed in the experimental section, and the proposed local best harmony search algorithm outperforms the genetic algorithm, immune algorithm and harmony search algorithm without local search. Moreover, six optimal solutions are given as Gantt charts, which vividly illustrate that the mathematical model established in this paper can facilitate the development of a better scheduling scheme.
机译：本文基于对结构金属制造工厂的调查，着重于两阶段的加工和焊接调度问题，旨在最大程度地减少总制造时间。在第一焊接阶段，根据经典的车间计划，将在第一阶段处理的几个零件分组为一个建筑构件。在第一阶段完成所有组成部分之前，无法开始制造建筑组件。本文建立了一个新的数学模型，主要通过考虑构造零件和相应零件之间的支配关系来使总建造时间最小化。为了解决这个两阶段问题，我们提出了一种改进的和声搜索算法。在每次迭代中将局部搜索方法应用于最佳矢量，以便可以随后实现更理想的矢量。在实验部分讨论了平均值，最小值，相对百分比偏差和标准偏差，并且所提出的局部最佳和声搜索算法优于遗传算法，免疫算法和没有局部搜索的和声搜索算法。此外，给出了六个最优解作为甘特图，生动地说明了本文建立的数学模型可以促进更好的调度方案的发展。

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