Loading [Contrib]/a11y/accessibility-menu.js

Special Issue: Optimization methods in Intelligent Manufacturing

Guest Editors

Prof. Xinyu Li
Huazhong University of Science & Technology, Wuhan, China
Email: lixinyu@mail.hust.edu.cn


Dr. Jin Yi
National University of Singapore, Singapore
Email: iseyij@nus.edu.sg


Dr. Junliang Wang
Donghua University, Shanghai, China
Email: Junliang.Wang2018@gmail.com

Manuscript Topics

Intelligent manufacturing is a main trend in the development of world manufacturing industry. United States proposes the intelligent manufacturing plan based on "Industrial Internet". German proposes the “Industry 4.0” plan to boost the competitiveness of the manufacturing industry through intelligent manufacturing. The intelligent manufacturing is also the main direction of the “Made in China 2025” plan. Moreover, Japan and some other big manufacturing countries also put forward the corresponding strategies for the development of intelligent manufacturing. The intelligent manufacturing becomes more and more popular in the manufacturing industry.

Optimization method is one of the key techniques for intelligent manufacturing to achieve its maximum performance including productivity, cost, quality, energy consumption and so on. This special issue aims to establish a forum for the discussion of recent progresses on the optimization methods in intelligent manufacturing. This special issue will publish original research, review and application papers including but not limited to the following fields:


•  Big Data and AI Driven Optimization Methods in Intelligent Manufacturing
•  CPS and Digital Twin in Intelligent Manufacturing
•  Optimization Methods in Intelligent Process Planning
•  Optimization Methods in Intelligent Manufacturing Process
•  Optimization Methods in Intelligent Fault Diagnosis
•  Optimization Methods in Intelligent Scheduling
•  Optimization Methods in Intelligent Manufacturing Systems
•  Optimization Methods in Sustainable Manufacturing and Re-Manufacturing
•  Applications of Optimization Methods in Intelligent Manufacturing
•  Other Related Topics on Optimization Methods in Intelligent Manufacturing


Instructions for authors
https://www.aimspress.com/mbe/news/solo-detail/instructionsforauthors
Please submit your manuscript to online submission system
http://oeps.aimspress.com/mbe/ch/author/login.aspx

Paper Submission

All manuscripts will be peer-reviewed before their acceptance for publication. The deadline for manuscript submission is 30 June 2019

Published Papers(14)

Research article
A parameterized shift-splitting preconditioner for saddle point problems
Li-Tao Zhang Chao-Qian Li Yao-Tang Li
2019, Volume 16, Issue 2: 1021-1033. doi: 10.3934/mbe.2019048
Abstract HTML PDF Cited (2) Viewed (5015)
Research article
A new ensemble residual convolutional neural network for remaining useful life estimation
Long Wen Yan Dong Liang Gao
2019, Volume 16, Issue 2: 862-880. doi: 10.3934/mbe.2019040
Abstract HTML PDF Cited (53) Viewed (8217)
Research article
A modified comprehensive learning particle swarm optimizer and its application in cylindricity error evaluation problem
Qing Wu Chunjiang Zhang Mengya Zhang Fajun Yang Liang Gao
2019, Volume 16, Issue 3: 1190-1209. doi: 10.3934/mbe.2019057
Abstract HTML PDF Cited (14) Viewed (5270)
Research article
A genetic regulatory network based method for multi-objective sequencing problem in mixed-model assembly lines
Youlong Lv Jie Zhang
2019, Volume 16, Issue 3: 1228-1243. doi: 10.3934/mbe.2019059
Abstract HTML PDF Cited (2) Viewed (4246)
Research article
Solving flexible job shop scheduling problems with transportation time based on improved genetic algorithm
Guohui Zhang Jinghe Sun Xing Liu Guodong Wang Yangyang Yang
2019, Volume 16, Issue 3: 1334-1347. doi: 10.3934/mbe.2019065
Abstract HTML PDF Cited (45) Viewed (9819)
Research article
A methodology for the modular structure planning of product-service systems
Hao Li Xiaoyu Wen Haoqi Wang Guofu Luo Steve Evans
2019, Volume 16, Issue 3: 1489-1524. doi: 10.3934/mbe.2019072
Abstract HTML PDF Cited (5) Viewed (4496)
Research article
An integrated approach for remanufacturing job shop scheduling with routing alternatives
Lingling Li Congbo Li Li Li Ying Tang Qingshan Yang
2019, Volume 16, Issue 4: 2063-2085. doi: 10.3934/mbe.2019101
Abstract HTML PDF Cited (9) Viewed (7456)
Research article
A literature review on latest developments of Harmony Search and its applications to intelligent manufacturing
Jin Yi Chao Lu Guomin Li
2019, Volume 16, Issue 4: 2086-2117. doi: 10.3934/mbe.2019102
Abstract HTML PDF Cited (23) Viewed (8365)
Research article
Research on multi-load AGV path planning of weaving workshop based on time priority
Li-zhen Du Shanfu Ke Zhen Wang Jing Tao Lianqing Yu Hongjun Li
2019, Volume 16, Issue 4: 2277-2292. doi: 10.3934/mbe.2019113
Abstract HTML PDF Cited (24) Viewed (5847)
Research article
A negative correlation ensemble transfer learning method for fault diagnosis based on convolutional neural network
Long Wen Liang Gao Yan Dong Zheng Zhu
2019, Volume 16, Issue 5: 3311-3330. doi: 10.3934/mbe.2019165
Abstract HTML PDF Cited (24) Viewed (7597)
Research article
A novel complex network based dynamic rule selection approach for open shop scheduling problem with release dates
Zilong Zhuang Zhiyao Lu Zizhao Huang Chengliang Liu Wei Qin
2019, Volume 16, Issue 5: 4491-4505. doi: 10.3934/mbe.2019224
Abstract HTML PDF Cited (12) Viewed (5017)
Research article
Tuning extreme learning machine by an improved electromagnetism-like mechanism algorithm for classification problem
Mengya Zhang Qing Wu Zezhou Xu
2019, Volume 16, Issue 5: 4692-4707. doi: 10.3934/mbe.2019235
Abstract HTML PDF Viewed (4261)
Research article
Reliability-based EDM process parameter optimization using kriging model and sequential sampling
Ma Jun Han Xinyu Xu Qian Chen Shiyou Zhao Wenbo Li Xiaoke
2019, Volume 16, Issue 6: 7421-7432. doi: 10.3934/mbe.2019371
Abstract HTML PDF Cited (4) Viewed (4632)