NDLI: Optimization of tandem cold rolling schedule based on competitive coevolution algorithm

Content Provider	IEEE Xplore Digital Library
Author	Zhao Xinqiu Meng Qinggang Che Haijun Yang Jingming
Copyright Year	2014
Description	Author affiliation: Nat. Eng. Res. Center for Equip. & Technol. of Cold Strip Rolling, Qinhuangdao, China (Zhao Xinqiu; Che Haijun; Yang Jingming) \|\| Key Lab. of Ind. Comput. Control Eng. of Hebei Province, Yanshan Univ., Qinhuangdao, China (Meng Qinggang)
Abstract	The schedule set is an important part in the cold rolling process, which directly affects product quality and production efficiency in the production of steel rolling. Due to the low precision of traditional rolling force model, a model of rolling force was founded by the least squares support vector machine (LSSVM) method though analyzing the influencing factors of rolling force. Considering the diversity of optimization goal on rolling schedule of cold tandem rolling, the rolling schedule was optimized by competitive coevolution algorithm (Comp-CEA). A rolling schedule of steel cold rolling mill in Tangshan was optimized by selecting the power distribution, excellent flatness and the slip rate as objective functions. The experiment results show that Comp-CEA has the advantages such as high accuracy, rapid convergence and so on, and three objective functions can be improved in varying degrees.
Starting Page	6500
Ending Page	6504
File Size	97619
Page Count	5
File Format	PDF
ISBN	9789881563873
ISSN	19341768
DOI	10.1109/ChiCC.2014.6896063
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-07-28
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	TCCT, CAA
Subject Keyword	rolling schedule Schedules Strips Comp-CEA LSSVM Force Sociology Linear programming Optimization tandem cold rolling
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Multi-objective optimization of rolling schedules for tandem cold rolling based on adaptive weight differential evolution algorithm

Multi-objective optimization of rolling schedules for tandem hot rolling based on opposition learning multi-objective genetic algorithm

Multi-objective optimization of rolling schedules for aluminum hot tandem rolling based on improved NSGA-II

Optimization of rolling schedules based on improved artificial fish swarm algorithm for aluminum strip hot rolling mills

Application of improved ant colony algorithm in load distribution optimization of tandem cold rolling

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

Optimization of schedule with multi-objective for tandem cold rolling mill based on IAGA

Optimization Design of Rolling Schedules with Rolling Force Self-learning

Multi-Objective Optimization of Rolling Schedule for Five-Stand Tandem Cold Mill

Optimization of tandem cold rolling schedule based on competitive coevolution algorithm

Similar Documents

Multi-objective optimization of rolling schedules for tandem cold rolling based on adaptive weight differential evolution algorithm

Multi-objective optimization of rolling schedules for tandem hot rolling based on opposition learning multi-objective genetic algorithm

Multi-objective optimization of rolling schedules for aluminum hot tandem rolling based on improved NSGA-II

Optimization of rolling schedules based on improved artificial fish swarm algorithm for aluminum strip hot rolling mills

Application of improved ant colony algorithm in load distribution optimization of tandem cold rolling

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

Optimization of schedule with multi-objective for tandem cold rolling mill based on IAGA

Optimization Design of Rolling Schedules with Rolling Force Self-learning

Multi-Objective Optimization of Rolling Schedule for Five-Stand Tandem Cold Mill

Optimization of tandem cold rolling schedule based on competitive coevolution algorithm