Constrained Multi-Objective Optimization With Deep Reinforcement Learning Assisted Operator Selection
Author:
Affiliation:
1. School of Computer Science, China University of Geosciences,Wuhan,China,430074
2. Tsinghua University,Department of Automation,Beijing,China,100084
3. Bielefeld University, North Rhine-Westphalia,Faculty of Technology,Bielefeld,Germany,33619
Funder
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/6570654/10475140/10482425.pdf?arnumber=10482425
Reference57 articles.
1. A Benchmark-Suite of real-World constrained multi-objective optimization problems and some baseline results
2. Evolutionary Multi-Objective Optimization for Web Service Location Allocation Problem
3. Shift-Based Penalty for Evolutionary Constrained Multiobjective Optimization and Its Application
4. A Coevolutionary Framework for Constrained Multiobjective Optimization Problems
5. Balancing Objective Optimization and Constraint Satisfaction in Constrained Evolutionary Multiobjective Optimization
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