Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
Robust multi-objective optimization of rolling schedule for tandem cold rolling based on evolutionary direction differential evolution algorithm
by
Fang, Lei
, Li, Yong
in
Applied and Technical Physics
/ Engineering
/ Evolutionary direction
/ Horizontal angle
/ Machines
/ Manufacturing
/ Materials Engineering
/ Materials Science
/ Metallic Materials
/ Mutation vector
/ Physical Chemistry
/ Processes
/ Robust multi-objective optimization
/ Rolling schedule
/ 优化目标函数
/ 冷连轧
/ 多目标优化模型
/ 差分进化算法
/ 拉丁超立方抽样
/ 轧制规程
/ 进化方向
/ 鲁棒性
2017
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Robust multi-objective optimization of rolling schedule for tandem cold rolling based on evolutionary direction differential evolution algorithm
by
Fang, Lei
, Li, Yong
in
Applied and Technical Physics
/ Engineering
/ Evolutionary direction
/ Horizontal angle
/ Machines
/ Manufacturing
/ Materials Engineering
/ Materials Science
/ Metallic Materials
/ Mutation vector
/ Physical Chemistry
/ Processes
/ Robust multi-objective optimization
/ Rolling schedule
/ 优化目标函数
/ 冷连轧
/ 多目标优化模型
/ 差分进化算法
/ 拉丁超立方抽样
/ 轧制规程
/ 进化方向
/ 鲁棒性
2017
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Robust multi-objective optimization of rolling schedule for tandem cold rolling based on evolutionary direction differential evolution algorithm
by
Fang, Lei
, Li, Yong
in
Applied and Technical Physics
/ Engineering
/ Evolutionary direction
/ Horizontal angle
/ Machines
/ Manufacturing
/ Materials Engineering
/ Materials Science
/ Metallic Materials
/ Mutation vector
/ Physical Chemistry
/ Processes
/ Robust multi-objective optimization
/ Rolling schedule
/ 优化目标函数
/ 冷连轧
/ 多目标优化模型
/ 差分进化算法
/ 拉丁超立方抽样
/ 轧制规程
/ 进化方向
/ 鲁棒性
2017
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Robust multi-objective optimization of rolling schedule for tandem cold rolling based on evolutionary direction differential evolution algorithm
Journal Article
Robust multi-objective optimization of rolling schedule for tandem cold rolling based on evolutionary direction differential evolution algorithm
2017
Request Book From Autostore
and Choose the Collection Method
Overview
According to the actual requirements, profile and rolling energy consumption are selected as objective functions of rolling schedule optimization for tandem cold rolling. Because of mechanical wear, roll diameter has some uncertainty during the rolling process, ignoring which will cause poor robustness of rolling schedule. In order to solve this problem, a robust multi-objective optimization model of rolling schedule for tandem cold rolling was established. A differential evolution algorithm based on the evolutionary direction was proposed. The algorithm calculated the horizontal angle of the vector, which was used to choose mutation vector. The chosen vector contained converging direction and it changed the random mutation operation in differential evolution algorithm. Efficiency of the proposed algorithm was verified by two benchmarks. Meanwhile, in order to ensure that delivery thicknesses have descending order like actual rolling schedule during evolution, a modified Latin Hypercube Sampling process was proposed. Finally, the proposed algorithm was applied to the model above. Results showed that profile was improved and rolling energy consumption was reduced compared with the actual rolling schedule. Meanwhile, robustness of solutions was ensured.
This website uses cookies to ensure you get the best experience on our website.