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首页> 外文期刊>International Journal of Industrial Engineering Computations >Parameters optimization of fabric finishing system of a textile industry using teaching–learning-based optimization algorithm
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Parameters optimization of fabric finishing system of a textile industry using teaching–learning-based optimization algorithm

机译:基于教学优化算法的纺织工业织物整理系统参数优化

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摘要

In the present work, a recently developed advanced optimization algorithm named as teaching–learning-based optimization (TLBO) is used for the parameters optimization of fabric finishing system of a textile industry. Fabric Finishing System has four main subsystems, arranged in hybrid configuration. For performance modeling and analysis of availability, a performance evaluating model of fabric finishing system has been developed with the help of mathematical formulation based on Markov-Birth-Death process using Probabilistic Approach. Then, the overall performance of the concerned system has first analyzed and then, optimized by using teaching–learning-based optimization (TLBO). The results of optimization using the proposed algorithm are validated by comparing with those obtained by using the genetic algorithm (GA) on the same system. Improvement in the results is obtained by the proposed algorithm. The results of effect of variation of the algorithm parameters on fitness values of the objective function are reported.
机译:在当前的工作中,最近开发的一种先进的优化算法,称为基于教学学习的优化(TLBO),被用于纺织工业织物整理系统的参数优化。织物整理系统具有四个主要子系统,以混合配置的方式排列。为了进行性能建模和可用性分析,借助基于概率方法的马尔可夫-出生-死亡过程的数学公式化,开发了织物整理系统的性能评估模型。然后,首先对有关系统的整体性能进行了分析,然后使用基于教学学习的优化(TLBO)进行了优化。通过与在同一系统上使用遗传算法(GA)获得的结果进行比较,验证了所提出算法的优化结果。所提出的算法对结果进行了改进。报告了算法参数变化对目标函数适应度值的影响结果。

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