A Multi-Objective Optimization Approach Based on an Enhanced Particle Swarm Optimization Algorithm With Evolutionary Game Theory
Author:
Affiliation:
1. School of Electrical and Mechanical Engineering, Pingdingshan University, Pingdingshan, China
2. School of Automation, Wuhan University of Technology, Wuhan, China
3. School of Economics and Management, Anhui Polytechnic University, Wuhu, China
Funder
Project of the Science and Technology Department of Henan Province
High-Level Talent Start-Up fund of Pingdingshan University
Research Project of Higher Education in Henan Province
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/ielx7/6287639/10005208/10190558.pdf?arnumber=10190558
Reference39 articles.
1. A competitive mechanism based multi-objective particle swarm optimizer with fast convergence
2. Robot path planning in uncertain environment using multi-objective particle swarm optimization
3. A decomposition-based multiobjective evolutionary algorithm with angle-based adaptive penalty
4. A new constraint handling method based on the modified Alopex-based evolutionary algorithm
5. MOPSOhv: A new hypervolume-based multi-objective particle swarm optimizer
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