Orthogonal Design-Based Control Vector Parameterization Combined With Improved Seagull Optimization Algorithm for Dynamic Optimization Problems
Author:
Affiliation:
1. School of Artificial Intelligence, Guangxi Minzu University, Nanning, China
2. College of Electronic Information, Guangxi Minzu University, Nanning, China
Funder
National Natural Science Foundation of China
Guangxi Natural Science Foundation
School Level Scientific Research Project
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/9668973/09799756.pdf?arnumber=9799756
Reference47 articles.
1. Dynamic Optimization of Industrial Processes With Nonuniform Discretization-Based Control Vector Parameterization
2. Dynamic optimization based on state transition algorithm for copper removal process
3. Optimal control strategies combined with PSO and control vector parameterization for batchwise chemical process;shi;CIESC Journal,2019
4. Solving 0–1 knapsack problems by chaotic monarch butterfly optimization algorithm with Gaussian mutation
5. A novel multi-scale cooperative mutation Fruit Fly Optimization Algorithm
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