A Self-Learning Based Dynamic Multi-Objective Evolutionary Algorithm for Resilient Scheduling Problems in Steelmaking Plants
Author:
Affiliation:
1. School of Materials Science and Engineering, Chongqing University, Chongqing, China
2. School of Automation, Chongqing University, Chongqing, China
3. Department of Chemical Engineering, University College London, London, U.K.
Funder
National Natural Science Foundation of China
Guangxi Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/8856/10094220/09772009.pdf?arnumber=9772009
Reference37 articles.
1. A distributionally robust scheduling approach for uncertain steelmaking and continuous casting processes;niu;IEEE Trans Syst Man Cybern Syst,2021
2. Adaptive Cross-Generation Differential Evolution Operators for Multiobjective Optimization
3. An Improved Differential Evolution Algorithm for Practical Dynamic Scheduling in Steelmaking-Continuous Casting Production
4. Shifting representation search for hybrid flexible flowline problems
5. Resilient design and operations of process systems: Nonlinear adaptive robust optimization model and algorithm for resilience analysis and enhancement
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