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Optimization Of Multi-objective Rolling Schedule Of Tandem Cold Rolling Based On Improved ABC Algorithm

Posted on:2015-11-06Degree:MasterType:Thesis
Country:ChinaCandidate:B LvFull Text:PDF
GTID:2298330452954799Subject:Systems Engineering
Abstract/Summary:PDF Full Text Request
At present, with the rapid development of modern industry, the requirement of theproduction and quality become increasingly higher in the production of cold rolled strip.Relying on experience can not achieve the quality control requirements, rolling scheduleoptimization is the fundamental way to solve this problem.Establishing a reasonablerolling schedule is not only an important condition of guaranteeing the high quality, highefficiency and low energy consumption of the cold rolling mill operation, but also is animportant technology issue of comprehensive optimization in cold rolling production. Theresearch works of this article aim at rolling schedules optimization of tandem cold rolling.The main job contents are as follows:Firstly, based on the production technology, basic construction and parameters offive-stand tandem cold mill and analysis of mathematical models in the tandem coldrolling process, the appropriate parameter models for tandem cold rolling are proposed.Secondly, in order to accelerate the rate of convergence and get better accuracy, aninitialization strategy based on the opposition-based learning is applied to make the initialindividuals even distribution in the search space, and tournament selection strategy isanalyzed and applied simultaneously. Meanwhile, the improved artificial colony algorithmis applied to rolling schedules of tandem cold rolling. A multi-objective optimized modelwas founded with equal load and overcome slide as object functions.Lastly, in order to avoid indetermination which is caused by weighting coefficient ofaggregate function multi-objective algorithm, the paper combine non-dominated sortingwith artificial bee colony algorithm,and get multi-objective artificial bee colony algorithm.A multi-objective optimized model was founded with minimize power consumption andovercome slide as object functions. Then, rolling schedule optimization is designed.
Keywords/Search Tags:rolling schedule optimization, artificial bee colony algorithm, opposition-based learning, selection strategy, multi-objective artificial beecolony algorithm
PDF Full Text Request
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