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MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition
  • Q. Zhang, H. Li
  • Mathematics, Computer Science
  • IEEE Transactions on Evolutionary Computation
  • 1 December 2007
Decomposition is a basic strategy in traditional multiobjective optimization. However, it has not yet been widely used in multiobjective evolutionary optimization. This paper proposes aExpand
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Multiobjective Optimization Problems With Complicated Pareto Sets, MOEA/D and NSGA-II
  • H. Li, Q. Zhang
  • Computer Science, Mathematics
  • IEEE Trans. Evol. Comput.
  • 1 February 2009
TLDR
We propose a general class of continuous multiobjective optimization test instances with arbitrary prescribed PS shapes. Expand
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  • 225
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Differential Evolution With Composite Trial Vector Generation Strategies and Control Parameters
TLDR
This paper studies whether the performance of differential evolution can be improved by combining several effective trial vector generation strategies with some suitable control parameter settings. Expand
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Multiobjective optimization Test Instances for the CEC 2009 Special Session and Competition
Multiobjective optimization Test Instances for the CEC 2009 Special Session and Competition Qingfu Zhang∗, Aimin Zhou∗, Shizheng Zhao†, Ponnuthurai Nagaratnam Suganthan†, Wudong Liu∗and SantoshExpand
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An Evolutionary Many-Objective Optimization Algorithm Based on Dominance and Decomposition
TLDR
Achieving balance between convergence and diversity is a key issue in evolutionary multiobjective optimization. Expand
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The performance of a new version of MOEA/D on CEC09 unconstrained MOP test instances
TLDR
This paper describes the idea of MOEA/D and proposes a strategy for allocating the computational resource to different subproblems in MOEA. Expand
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RM-MEDA: A Regularity Model-Based Multiobjective Estimation of Distribution Algorithm
  • Q. Zhang, A. Zhou, Y. Jin
  • Mathematics, Computer Science
  • IEEE Transactions on Evolutionary Computation
  • 1 February 2008
TLDR
We propose a regularity model-based multiobjective estimation of distribution algorithm (RM-MEDA) for continuous multi objective optimization problems with variable linkages. Expand
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Multiobjective evolutionary algorithms: A survey of the state of the art
TLDR
This paper surveys the development of multiobjective evolutionary algorithms (MOEAs) primarily during eight years. Expand
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Decomposition of a Multiobjective Optimization Problem Into a Number of Simple Multiobjective Subproblems
TLDR
We propose MOEA/D-M2M, a new version of multiobjective optimization evolutionary algorithm-based decomposition. Expand
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Adaptive Operator Selection With Bandits for a Multiobjective Evolutionary Algorithm Based on Decomposition
TLDR
We propose a bandit-based AOS method, fitness-rate-rank-based multiarmed bandit (FRRMAB). Expand
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