Q. Zhang

Publications
Influence

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 a… Expand

4,171
808
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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

We propose a general class of continuous multiobjective optimization test instances with arbitrary prescribed PS shapes. Expand

1,504
225
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Differential Evolution With Composite Trial Vector Generation Strategies and Control Parameters

Y. Wang, Zixing Cai, Q. Zhang
Mathematics, Computer Science
IEEE Transactions on Evolutionary Computation
1 February 2011

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

Multiobjective optimization Test Instances for the CEC 2009 Special Session and Competition

Q. Zhang, A. Zhou, Shi-Zheng Zhao, P. Suganthan, Wudong Liu, Santosh Tiwari
Computer Science
2009

Multiobjective optimization Test Instances for the CEC 2009 Special Session and Competition Qingfu Zhang∗, Aimin Zhou∗, Shizheng Zhao†, Ponnuthurai Nagaratnam Suganthan†, Wudong Liu∗and Santosh… Expand

An Evolutionary Many-Objective Optimization Algorithm Based on Dominance and Decomposition

Ke Li, K. Deb, Q. Zhang, S. Kwong
Mathematics, Computer Science
IEEE Transactions on Evolutionary Computation
1 October 2015

Achieving balance between convergence and diversity is a key issue in evolutionary multiobjective optimization. Expand

The performance of a new version of MOEA/D on CEC09 unconstrained MOP test instances

Q. Zhang, Wudong Liu, H. Li
Computer Science
IEEE Congress on Evolutionary Computation
18 May 2009

This paper describes the idea of MOEA/D and proposes a strategy for allocating the computational resource to different subproblems in MOEA. Expand

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

We propose a regularity model-based multiobjective estimation of distribution algorithm (RM-MEDA) for continuous multi objective optimization problems with variable linkages. Expand

Multiobjective evolutionary algorithms: A survey of the state of the art

A. Zhou, B. Qu, H. Li, Shi-Zheng Zhao, P. Suganthan, Q. Zhang
Computer Science
Swarm Evol. Comput.
1 March 2011

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

Hai-Lin Liu, Fangqing Gu, Q. Zhang
Mathematics, Computer Science
IEEE Transactions on Evolutionary Computation
2014

We propose MOEA/D-M2M, a new version of multiobjective optimization evolutionary algorithm-based decomposition. Expand

Adaptive Operator Selection With Bandits for a Multiobjective Evolutionary Algorithm Based on Decomposition

Ke Li, Álvaro Fialho, S. Kwong, Q. Zhang
Mathematics, Computer Science
IEEE Transactions on Evolutionary Computation
1 February 2014

We propose a bandit-based AOS method, fitness-rate-rank-based multiarmed bandit (FRRMAB). Expand

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