首页> 外文期刊>The International Journal of Advanced Manufacturing Technology >Adaptation of the simulated annealing optimization algorithm to achieve improved near-optimum objective function values and computation times for multiple component manufacture
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Adaptation of the simulated annealing optimization algorithm to achieve improved near-optimum objective function values and computation times for multiple component manufacture

机译:调整模拟退火优化算法以实现多部件制造的改进的近最佳目标函数值和计算时间

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摘要

The paper concerns the development of the Simulated Annealing Algorithm (SAA) for the sequencing of cutter tool movement in machine tools capable of manufacturing many components, located on a box-like jig/pallet, in a single setting using a multiple tool magazine. The objective of the SAA is to minimise the total machine tool residence time. The general SAA has been enhanced, to achieve lower values of the objective function during the iterative scheme, and hence improve solution accuracy; and, to reduce computation time by cessation of the iterative scheme when no further improvement in the objective function occurs. The reconfigured SAA has been evaluated using a number of case studies. The results show that a reduction in the objective function value can be achieved in up to 6%, with far less computational effort. In addition, it is shown that the computation time can be reduced by a factor of between 20% and 72%. The improvement in the objective function value and the computational speed depends on the complexity of the problem posed to the SAA software.
机译:本文关注于模拟退火算法(SAA)的发展,该算法用于在机床中对刀具运动进行排序,该机床能够使用多刀库在单个设置中以单个设置制造位于箱形夹具/托盘上的许多组件。 SAA的目标是最大程度地减少机床的总停留时间。增强了通用SAA,以在迭代方案中实现较低的目标函数值,从而提高了求解精度;当目标函数没有进一步改善时,通过停止迭代方案来减少计算时间。已使用许多案例研究对重新配置的SAA进行了评估。结果表明,目标函数值的降低最多可以达到6%,而计算工作量则要少得多。此外,显示出可以将计算时间减少20%至72%。目标函数值和计算速度的提高取决于SAA软件所面临问题的复杂性。

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