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1.

Parameters optimization of fabric finishing system of a textile industry using teaching–learning-based optimization algorithm Pages 221-234 Right click to download the paper Download PDF

Authors: Rajiv Kumar, P.C. Tewari, Dinesh Khanduja

doi 10.5267/j.ijiec.2017.6.002 Crossmark

Keywords: Performance modeling, TLBO, Markov process, Genetic algorithm, Probabilistic Approach

Abstract:
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.
Details
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Journal: IJIEC | Year: 2018 | Volume: 9 | Issue: 2 | Views: 2616 | Reviews: 0

 

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