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Multi-objective Optimization Of Rolling Schedule Based On The Improved Quantum Genetic

Posted on:2016-04-23Degree:MasterType:Thesis
Country:ChinaCandidate:J Q GuFull Text:PDF
GTID:2191330479450613Subject:Control theory and control engineering
Abstract/Summary:PDF Full Text Request
With the rapid development of aluminum industry, aluminum alloy has been applied in various fields, and has become one of the pillar industries in most countries and regions. Aluminum hot tandem rolling process is more complex. What’s more, a reasonable rolling schedule is an important requirement which can ensure that aluminum hot tandem mill production is high quality, high efficiency and low consumption. This subject is currently an important comprehensive optimization technology subject. In recent years, with the development of industry, with the increasingly high demand of quality of aluminum, the requirement of production is increasingly high. Therefore, improving the optimization ability of rolling schedule is the problem to be solved.First of all, studying the chaotic characteristics of chaotic map tent, and using it in the initialization and mutation. At the same time, using Gauss variance improved single objective optimization algorithm. Through the traditional function test, convergence and global searching ability of the algorithm are verified.Secondly, through combining quantum genetic single objective optimization algorithm with multi-objective optimization theory putting forward a kind of improved quantum genetic algorithm for multi objective optimization. The improved method includes adaptive grid update mechanism, the optimal individual selection mechanism, Gauss mutation, tent chaotic map. Through solving the test functions, the convergence and distribution of the improved algorithm are verified.Finally, Taking same relative load, preventing slippage and good shape at the end of the frame as the target, establishes multi objective model of the aluminum hot tandem rolling load. Taking aluminum hot tandem rolling as the background, based on actual data in the field establish a set of rolling rules which satisfies the constraints on the rolling schedule optimization. At the same time, using the improved quantum genetic algorithm optimize this schedule. The results show that, Pareto frontier for decision makers provided the pressure conditions permit, and can choose the suitable pressure according to the requirement of rate as the current setting value. Simulation results show that this procedure on two set of guiding significance calculation.
Keywords/Search Tags:quantum genetic algorithm, multi-objective optimization, adaptive grid, rolling schedule, chaos map
PDF Full Text Request
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