Optimization of Rolling Schedule in Tandem Cold Mill Based on QPSO Algorithm

Sen Lin; Yu Rong Nan

doi:10.4028/www.scientific.net/AMR.145.165

Paper Titles

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Online Quality Prediction of Strip Hot-Dip Galvanizing Based on Support Vector Regression
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Analysis of the Mill Roller Bearing Using Mixed Fast Multipole Boundary Element Method
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Optimization of Rolling Schedule in Tandem Cold Mill Based on QPSO Algorithm
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The Development of Short Stress Path Experimental Asymmetric Multifunctional Rolling Mill
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Analysis on Diffusion Parameters of Rolling Mill Bearing Alloy-Interface
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Finite Element Simulation of the Hot-Rolling Process of Titanium Alloy Bar
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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 145Optimization of Rolling Schedule in Tandem Cold...

Optimization of Rolling Schedule in Tandem Cold Mill Based on QPSO Algorithm

Abstract:

This paper adopts equal relatively load as objective function, and makes every parameter to meet certain restrictive conditions. SUMT algorithm was used to change constraints to non-binding conditions. QPSO algorithm was applied to optimize objective functions to obtain optimal solution. This algorithm was based on classical particle swarm optimization, which, with the conduct of quantum particle, had effective global search capability, good convergence and stability. As a result, reasonable distribution of tandem cold rolling power and full use of equipment capacity were realized, resulting in the improvement of production efficiency.

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Periodical:

Advanced Materials Research (Volume 145)

Pages:

165-170

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.145.165

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Online since:

October 2010

Authors:

Sen Lin, Yu Rong Nan

Keywords:

Quantum Particle Swarm Optimization, Schedule Optimization, Sequential Unconstrained Minimization Technique, Tandem Cold Rolling

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