People

Professor Qingfu Zhang

Visiting Professor
School of Computer Science and Electronic Engineering
Professor Qingfu Zhang

Teaching and supervision

Previous supervision

Hamid Reza Jalalian
Hamid Reza Jalalian
Thesis title: Decomposition Evolutionary Algorithms for Noisy Multiobjective Optimization
Degree subject: Computing and Electronic Systems
Degree type: Doctor of Philosophy
Awarded date: 6/6/2016
Ahmad Hasan Y Alhindi
Ahmad Hasan Y Alhindi
Thesis title: Combining Moea/D with Local Search
Degree subject: Computing and Electronic Systems
Degree type: Doctor of Philosophy
Awarded date: 12/5/2015
Rashida Adeeb Khanum
Rashida Adeeb Khanum
Thesis title: Hybrid Evolutionary Algorithms and Local Search Techniques
Degree subject: Mathematics
Degree type: Doctor of Philosophy
Awarded date: 12/2/2013
Nasser Mansoor M Tairan
Nasser Mansoor M Tairan
Thesis title: Cooperative Guided Local Search
Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 26/9/2012
Wali Khan
Wali Khan
Thesis title: Hybrid Multiobjective Evolutionary Algorithms Based on Decomposition
Degree subject: Mathematics
Degree type: Doctor of Philosophy
Awarded date: 16/1/2012
Muhammad Asif Jan
Muhammad Asif Jan
Thesis title: Decomposition Based Evolutionary Methods for Constrained Multiobjective Optimization
Degree subject: Mathematics
Degree type: Doctor of Philosophy
Awarded date: 20/12/2011

Publications

Journal articles (119)

Wang, J., Weng, T. and Zhang, Q., (2019). A Two-Stage Multiobjective Evolutionary Algorithm for Multiobjective Multidepot Vehicle Routing Problem With Time Windows. IEEE Transactions on Cybernetics. 49 (7), 2467-2478

Sun, J., Zhang, H., Zhou, A., Zhang, Q. and Zhang, K., (2019). A new learning-based adaptive multi-objective evolutionary algorithm. Swarm and Evolutionary Computation. 44, 304-319

Cai, X., Sun, H., Zhang, Q. and Huang, Y., (2019). A Grid Weighted Sum Pareto Local Search for Combinatorial Multi and Many-Objective Optimization. IEEE Transactions on Cybernetics. 49 (9), 3586-3598

Wu, M., Li, K., Kwong, S., Zhang, Q. and Zhang, J., (2019). Learning to Decompose: A Paradigm for Decomposition-Based Multiobjective Optimization. IEEE Transactions on Evolutionary Computation. 23 (3), 376-390

He, X., Zhou, Y., Chen, Z. and Zhang, Q., (2019). Evolutionary Many-Objective Optimization Based on Dynamical Decomposition. IEEE Transactions on Evolutionary Computation. 23 (3), 361-375

Sun, J., Zhang, H., Zhou, A., Zhang, Q., Zhang, K., Tu, Z. and Ye, K., (2019). Learning From a Stream of Nonstationary and Dependent Data in Multiobjective Evolutionary Optimization. IEEE Transactions on Evolutionary Computation. 23 (4), 541-555

Ma, X., Li, X., Zhang, Q., Tang, K., Liang, Z., Xie, W. and Zhu, Z., (2019). A Survey on Cooperative Co-Evolutionary Algorithms. IEEE Transactions on Evolutionary Computation. 23 (3), 421-441

Wang, Z., Ong, Y-S., Sun, J., Gupta, A. and Zhang, Q., (2019). A Generator for Multiobjective Test Problems With Difficult-to-Approximate Pareto Front Boundaries. IEEE Transactions on Evolutionary Computation. 23 (4), 556-571

Fan, Z., Li, W., Cai, X., Li, H., Wei, C., Zhang, Q., Deb, K. and Goodman, E., (2019). Push and pull search for solving constrained multi-objective optimization problems. Swarm and Evolutionary Computation. 44, 665-679

Li, H., Deng, J., Zhang, Q. and Sun, J., (2019). Adaptive Epsilon dominance in decomposition-based multiobjective evolutionary algorithm. Swarm and Evolutionary Computation. 45, 52-67

Deng, J. and Zhang, Q., (2019). Approximating Hypervolume and Hypervolume Contributions Using Polar Coordinate. IEEE Transactions on Evolutionary Computation, 1-1

Li, H., Deb, K. and Zhang, Q., (2019). Variable-length Pareto Optimization via Decomposition-based Evolutionary Multiobjective Algorithm. IEEE Transactions on Evolutionary Computation, 1-1

Wang, W., Yang, S., Lin, Q., Zhang, Q., Wong, K-C., Coello Coello, CA. and Chen, J., (2019). An Effective Ensemble Framework for Multiobjective Optimization. IEEE Transactions on Evolutionary Computation. 23 (4), 645-659

Li, H., Deb, K., Zhang, Q., Suganthan, PN. and Chen, L., (2019). Comparison between MOEA/D and NSGA-III on a set of novel many and multi-objective benchmark problems with challenging difficulties. Swarm and Evolutionary Computation. 46, 104-117

Zhang, H., Sun, J., Liu, T., Zhang, K. and Zhang, Q., (2019). Balancing exploration and exploitation in multiobjective evolutionary optimization. Information Sciences. 497, 129-148

Liu, H-L., Chen, L., Zhang, Q. and Deb, K., (2018). Adaptively Allocating Search Effort in Challenging Many-Objective Optimization Problems. IEEE Transactions on Evolutionary Computation. 22 (3), 433-448

Li, H., Zhang, Q., Deng, J. and Xu, Z-B., (2018). A Preference-Based Multiobjective Evolutionary Approach for Sparse Optimization. IEEE Transactions on Neural Networks and Learning Systems. 29 (5), 1716-1731

Shi, J., Zhang, Q. and Tsang, E., (2018). EB-GLS: an improved guided local search based on the big valley structure. Memetic Computing. 10 (3), 333-350

Jiang, Y., Liu, Y., Shang, J., Yildirim, P. and Zhang, Q., (2018). Optimizing online recurring promotions for dual-channel retailers: Segmented markets with multiple objectives. European Journal of Operational Research. 267 (2), 612-627

Li, Z. and Zhang, Q., (2018). A Simple Yet Efficient Evolution Strategy for Large-Scale Black-Box Optimization. IEEE Transactions on Evolutionary Computation. 22 (5), 637-646

Cai, X., Mei, Z., Fan, Z. and Zhang, Q., (2018). A Constrained Decomposition Approach With Grids for Evolutionary Multiobjective Optimization. IEEE Transactions on Evolutionary Computation. 22 (4), 564-577

Fu, X., Sun, J. and Zhang, Q., (2018). A Reference-Inspired Evolutionary Algorithm with Subregion Decomposition for Many-Objective Optimization. Advances in Intelligent Systems and Computing. 650, 145-156

Li, H., Sun, J., Fan, Y., Wang, M. and Zhang, Q., (2018). A New Steady-State MOEA/D for Sparse Optimization. Advances in Intelligent Systems and Computing. 650, 119-131

Shi, J. and Zhang, Q., (2018). A new cooperative framework for parallel trajectory-based metaheuristics. Applied Soft Computing. 65, 374-386

Ma, X., Zhang, Q., Tian, G., Yang, J. and Zhu, Z., (2018). On Tchebycheff Decomposition Approaches for Multiobjective Evolutionary Optimization. IEEE Transactions on Evolutionary Computation. 22 (2), 226-244

Ding, D., Zhang, Q., Xia, J., Zhou, A. and Yang, L., (2018). Wiggly Parallel-Coupled Line Design by Using Multiobjective Evolutionay Algorithm. IEEE Microwave and Wireless Components Letters. 28 (8), 648-650

Li, H., Sun, J., Wang, M. and Zhang, Q., (2018). MOEA/D with chain-based random local search for sparse optimization. Soft Computing. 22 (21), 7087-7102

Wang, B-C., Li, H-X., Zhang, Q. and Wang, Y., (2018). Decomposition-Based Multiobjective Optimization for Constrained Evolutionary Optimization. IEEE Transactions on Systems Man and Cybernetics: Systems, 1-14

Li, Z., Zhang, Q., Lin, X. and Zhen, H-L., (2018). Fast Covariance Matrix Adaptation for Large-Scale Black-Box Optimization. IEEE Transactions on Cybernetics, 1-11

Shi, J., Zhang, Q. and Sun, J., (2018). PPLS/D: Parallel Pareto Local Search Based on Decomposition. IEEE Transactions on Cybernetics, 1-12

Wu, M., Li, K., Kwong, S. and Zhang, Q., (2018). Evolutionary Many-Objective Optimization Based on Adversarial Decomposition. IEEE Transactions on Cybernetics, 1-12

Shi, J. and Zhang, Q., (2018). Corrigendum to “A new cooperative framework for parallel trajectory-based metaheuristics” [Applied Soft Computing 65 (2018) 374–386]. Applied Soft Computing. 70, 946-946

Wang, Z., Zhang, Q., Li, H., Ishibuchi, H. and Jiao, L., (2017). On the use of two reference points in decomposition based multiobjective evolutionary algorithms. Swarm and Evolutionary Computation. 34, 89-102

Li, H., Zhang, Q. and Deng, J., (2017). Biased Multiobjective Optimization and Decomposition Algorithm. IEEE Transactions on Cybernetics. 47 (1), 52-66

Zhou, Y., Kwong, S., Guo, H., Zhang, X. and Zhang, Q., (2017). A Two-Phase Evolutionary Approach for Compressive Sensing Reconstruction. IEEE Transactions on Cybernetics. 47 (9), 2651-2663

Li, K., Deb, K., Zhang, Q. and Zhang, Q., (2017). Efficient Nondomination Level Update Method for Steady-State Evolutionary Multiobjective Optimization. IEEE Transactions on Cybernetics. 47 (9), 2838-2849

Cai, X., Yang, Z., Fan, Z. and Zhang, Q., (2017). Decomposition-Based-Sorting and Angle-Based-Selection for Evolutionary Multiobjective and Many-Objective Optimization. IEEE Transactions on Cybernetics. 47 (9), 2824-2837

Lai, X., Zhou, Y., Xia, X. and Zhang, Q., (2017). Performance Analysis of Evolutionary Algorithms for Steiner Tree Problems. Evolutionary Computation. 25 (4), 707-723

Wu, M., Li, K., Kwong, S., Zhou, Y. and Zhang, Q., (2017). Matching-Based Selection With Incomplete Lists for Decomposition Multiobjective Optimization. IEEE Transactions on Evolutionary Computation. 21 (4), 554-568

Wang, L., Zhang, Q., Zhou, A., Gong, M. and Jiao, L., (2016). Constrained Subproblems in a Decomposition-Based Multiobjective Evolutionary Algorithm. IEEE Transactions on Evolutionary Computation. 20 (3), 475-480

Wang, H., Zhang, Q., Jiao, L. and Yao, X., (2016). Regularity Model for Noisy Multiobjective Optimization. IEEE Transactions on Cybernetics. 46 (9), 1997-2009

Liu, B., Koziel, S. and Zhang, Q., (2016). A multi-fidelity surrogate-model-assisted evolutionary algorithm for computationally expensive optimization problems. Journal of Computational Science. 12, 28-37

Zhou, A. and Zhang, Q., (2016). Are All the Subproblems Equally Important? Resource Allocation in Decomposition-Based Multiobjective Evolutionary Algorithms. IEEE Transactions on Evolutionary Computation. 20 (1), 52-64

Li, H., Zhang, Q., Chen, Q., Zhang, L. and Jiao, Y-C., (2016). Multiobjective differential evolution algorithm based on decomposition for a type of multiobjective bilevel programming problems. Knowledge-Based Systems. 107, 271-288

Saxena, DK., Sinha, A., Duro, JA. and Zhang, Q., (2016). Entropy-Based Termination Criterion for Multiobjective Evolutionary Algorithms. IEEE Transactions on Evolutionary Computation. 20 (4), 485-498

Wang, Z., Zhang, Q., Zhou, A., Gong, M. and Jiao, L., (2016). Adaptive Replacement Strategies for MOEA/D. IEEE Transactions on Cybernetics. 46 (2), 474-486

Zhang, H., Zhou, A., Song, S., Zhang, Q., Gao, X-Z. and Zhang, J., (2016). A Self-Organizing Multiobjective Evolutionary Algorithm. IEEE Transactions on Evolutionary Computation. 20 (5), 792-806

Wang, R., Zhang, Q. and Zhang, T., (2016). Decomposition-Based Algorithms Using Pareto Adaptive Scalarizing Methods. IEEE Transactions on Evolutionary Computation. 20 (6), 821-837

Zhang, X., Zhou, Y., Zhang, Q., Lee, VCS. and Li, M., (2016). Problem Specific MOEA/D for Barrier Coverage with Wireless Sensors. IEEE Transactions on Cybernetics. 47 (11), 1-12

Zhu, Z., Xiao, J., Li, J-Q., Wang, F. and Zhang, Q., (2015). Global path planning of wheeled robots using multi-objective memetic algorithms. Integrated Computer-Aided Engineering. 22 (4), 387-404

Rubio-Largo, Á., Zhang, Q. and Vega-Rodríguez, MA., (2015). Multiobjective evolutionary algorithm based on decomposition for 3-objective optimization problems with objectives in different scales. Soft Computing. 19 (1), 157-166

Xinye Cai, Yexing Li, Zhun Fan and Qingfu Zhang, (2015). An External Archive Guided Multiobjective Evolutionary Algorithm Based on Decomposition for Combinatorial Optimization. IEEE Transactions on Evolutionary Computation. 19 (4), 508-523

Feng, Z., Zhang, Q., Zhang, Q., Tang, Q., Yang, T. and Ma, Y., (2015). A multiobjective optimization based framework to balance the global exploration and local exploitation in expensive optimization. Journal of Global Optimization. 61 (4), 677-694

Li, K., Kwong, S., Zhang, Q. and Deb, K., (2015). Interrelationship-Based Selection for Decomposition Multiobjective Optimization. IEEE Transactions on Cybernetics. 45 (10), 2076-2088

Li, K., Deb, K., Zhang, Q. and Kwong, S., (2015). An Evolutionary Many-Objective Optimization Algorithm Based on Dominance and Decomposition. IEEE Transactions on Evolutionary Computation. 19 (5), 694-716

Zhou, A., Sun, J. and Zhang, Q., (2015). An Estimation of Distribution Algorithm With Cheap and Expensive Local Search Methods. IEEE Transactions on Evolutionary Computation. 19 (6), 807-822

Gong, Y-J., Chen, W-N., Zhan, Z-H., Zhang, J., Li, Y., Zhang, Q. and Li, J-J., (2015). Distributed evolutionary algorithms and their models: A survey of the state-of-the-art. Applied Soft Computing. 34, 286-300

Liao, S. and Zhang, Q., (2015). A Multiutility Framework With Application for Studying Tradeoff Between Utility and Lifetime in Wireless Sensor Networks. IEEE Transactions on Vehicular Technology. 64 (10), 4701-4711

Zhao, X., Lin, W. and Zhang, Q., (2014). Enhanced particle swarm optimization based on principal component analysis and line search. Applied Mathematics and Computation. 229, 440-456

Li, K., Fialho, A., Kwong, S. and Zhang, Q., (2014). Adaptive Operator Selection With Bandits for a Multiobjective Evolutionary Algorithm Based on Decomposition. IEEE Transactions on Evolutionary Computation. 18 (1), 114-130

Liu, B., Zhang, Q. and Gielen, GGE., (2014). A Gaussian Process Surrogate Model Assisted Evolutionary Algorithm for Medium Scale Expensive Optimization Problems. IEEE Transactions on Evolutionary Computation. 18 (2), 180-192

Zhou, AM., Zhang, QF. and Zhang, GX., (2014). Multiobjective evolutionary algorithm based on mixture Gaussian models. Ruan Jian Xue Bao/Journal of Software. 25 (5), 913-928

Kwong, S. and Zhang, Q., (2014). Bridging machine learning and evolutionary computation. Neurocomputing. 146, 1-1

Liu, H-L., Gu, F. and Zhang, Q., (2014). Decomposition of a Multiobjective Optimization Problem Into a Number of Simple Multiobjective Subproblems. IEEE Transactions on Evolutionary Computation. 18 (3), 450-455

Duro, JA., Kumar Saxena, D., Deb, K. and Zhang, Q., (2014). Machine learning based decision support for many-objective optimization problems. Neurocomputing. 146, 30-47

Liangjun Ke, Qingfu Zhang and Battiti, R., (2014). Hybridization of Decomposition and Local Search for Multiobjective Optimization. IEEE Transactions on Cybernetics. 44 (10), 1808-1820

Rubio-Largo, Á., Zhang, Q. and Vega-Rodríguez, MA., (2014). A multiobjective evolutionary algorithm based on decomposition with normal boundary intersection for traffic grooming in optical networks. Information Sciences. 289 (1), 91-116

Jianyong Sun, Qingfu Zhang and Xin Yao, (2014). Meta-Heuristic Combining Prior Online and Offline Information for the Quadratic Assignment Problem. IEEE Transactions on Cybernetics. 44 (3), 429-444

Ke Li, Qingfu Zhang, Sam Kwong, Miqing Li and Ran Wang, (2014). Stable Matching-Based Selection in Evolutionary Multiobjective Optimization. IEEE Transactions on Evolutionary Computation. 18 (6), 909-923

Aimin Zhou, Yaochu Jin and Qingfu Zhang, (2014). A Population Prediction Strategy for Evolutionary Dynamic Multiobjective Optimization. IEEE Transactions on Cybernetics. 44 (1), 40-53

Sun, J., Garibaldi, JM., Krasnogor, N. and Zhang, Q., (2013). An Intelligent Multi-Restart Memetic Algorithm for Box Constrained Global Optimisation. Evolutionary Computation. 21 (1), 107-147

Saxena, DK., Duro, JA., Tiwari, A., Deb, K. and Zhang, Q., (2013). Objective Reduction in Many-Objective Optimization: Linear and Nonlinear Algorithms. IEEE Transactions on Evolutionary Computation. 17 (1), 77-99

Gong, M., Chen, X., Ma, L., Zhang, Q. and Jiao, L., (2013). Identification of multi-resolution network structures with multi-objective immune algorithm. Applied Soft Computing. 13 (4), 1705-1717

Liao, S. and Zhang, Q., (2013). Approximation for combinatorial network optimisation using Tsallis entropy. Electronics Letters. 49 (14), 882-884

Ke, L., Zhang, Q. and Battiti, R., (2013). MOEA/D-ACO: A Multiobjective Evolutionary Algorithm Using Decomposition and AntColony. IEEE Transactions on Cybernetics. 43 (6), 1845-1859

Liu, B., Zhang, Q., Fernandez, FV. and Gielen, GGE., (2013). An Efficient Evolutionary Algorithm for Chance-Constrained Bi-Objective Stochastic Optimization. IEEE Transactions on Evolutionary Computation. 17 (6), 786-796

Brownlee, AEI., McCall, JAW. and Zhang, Q., (2013). Fitness Modeling With Markov Networks. IEEE Transactions on Evolutionary Computation. 17 (6), 862-879

Chen, S-H., Chang, P-C., Cheng, TCE. and Zhang, Q., (2012). A Self-guided Genetic Algorithm for permutation flowshop scheduling problems. Computers & Operations Research. 39 (7), 1450-1457

Wang, Y., Cai, Z. and Zhang, Q., (2012). Enhancing the search ability of differential evolution through orthogonal crossover. Information Sciences. 185 (1), 153-177

Jaszkiewicz, A., Ishibuchi, H. and Zhang, Q., (2012). Multiobjective Memetic Algorithms. Studies in Computational Intelligence. 379, 201-217

Gong, M., Ma, L., Zhang, Q. and Jiao, L., (2012). Community detection in networks by using multiobjective evolutionary algorithm with decomposition. Physica A: Statistical Mechanics and its Applications. 391 (15), 4050-4060

Zhao, S-Z., Suganthan, PN. and Zhang, Q., (2012). Decomposition-Based Multiobjective Evolutionary Algorithm With an Ensemble of Neighborhood Sizes. IEEE Transactions on Evolutionary Computation. 16 (3), 442-446

Wang, Y., Cai, Z. and Zhang, Q., (2011). Differential Evolution With Composite Trial Vector Generation Strategies and Control Parameters. IEEE Transactions on Evolutionary Computation. 15 (1), 55-66

Zhou, A., Qu, B-Y., Li, H., Zhao, S-Z., Suganthan, PN. and Zhang, Q., (2011). Multiobjective evolutionary algorithms: A survey of the state of the art. Swarm and Evolutionary Computation. 1 (1), 32-49

Konstantinidis, A., Yang, K., Zhang, Q. and Zeinalipour-Yazti, D., (2010). A multi-objective evolutionary algorithm for the deployment and power assignment problem in wireless sensor networks. Computer Networks. 54 (6), 960-976

Chen, S-H., Chen, M-C., Chang, P-C., Zhang, Q. and Chen, Y-M., (2010). Guidelines for developing effective Estimation of Distribution Algorithms in solving single machine scheduling problems. Expert Systems with Applications. 37 (9), 6441-6451

Qingfu Zhang, Wudong Liu, Tsang, E. and Virginas, B., (2010). Expensive Multiobjective Optimization by MOEA/D With Gaussian Process Model. IEEE Transactions on Evolutionary Computation. 14 (3), 456-474

Sun, J., Zhang, Q. and Li, J., (2010). Two-level evolutionary approach to the survivable mesh-based transport network topological design. Journal of Heuristics. 16 (5), 723-744

Hui Li and Qingfu Zhang, (2009). Multiobjective Optimization Problems With Complicated Pareto Sets, MOEA/D and NSGA-II. IEEE Transactions on Evolutionary Computation. 13 (2), 284-302

Peng, W., Zhang, Q. and Li, H., (2009). Comparison between MOEA/D and NSGA-II on the Multi-Objective Travelling Salesman Problem. Studies in Computational Intelligence. 171, 309-324

Aimin Zhou, Qingfu Zhang and Yaochu Jin, (2009). Approximating the Set of Pareto-Optimal Solutions in Both the Decision and Objective Spaces by an Estimation of Distribution Algorithm. IEEE Transactions on Evolutionary Computation. 13 (5), 1167-1189

Yao, J., Zhang, Q. and Lei, J., (2009). Recent developments in natural computation. Neurocomputing. 72 (13-15), 2833-2834

Lozano, JA., Qingfu Zhang and Larraaga, P., (2009). Guest Editorial: Special Issue on Evolutionary Algorithms Based on Probabilistic Models. IEEE Transactions on Evolutionary Computation. 13 (6), 1197-1198

Qingfu Zhang, Aimin Zhou and Yaochu Jin, (2008). RM-MEDA: A Regularity Model-Based Multiobjective Estimation of Distribution Algorithm. IEEE Transactions on Evolutionary Computation. 12 (1), 41-63

Meng, D., Leung, Y., Xu, Z., Fung, T. and Zhang, Q., (2008). Improving geodesic distance estimation based on locally linear assumption. Pattern Recognition Letters. 29 (7), 862-870

Zhang, Q., Zhou, A. and Jin, Y., (2008). Errata to “RM-MEDA: A Regularity Model-Based Multiobjective Estimation of Distribution Algorithm” [Feb 08 41-63]. IEEE Transactions on Evolutionary Computation. 12 (3), 392-392

SUN, JIANYONG., ZHANG, QINGFU., LI, JIN. and YAO, XIN., (2008). A HYBRID ESTIMATION OF DISTRIBUTION ALGORITHM FOR CDMA CELLULAR SYSTEM DESIGN. International Journal of Computational Intelligence and Applications. 07 (02), 187-200

Konstantinidis, A., Yang, K., Chen, H-H. and Zhang, Q., (2007). Energy-aware topology control for wireless sensor networks using memetic algorithms. Computer Communications. 30 (14-15), 2753-2764

Zhang, Q., Sun, J., Xiao, G. and Tsang, E., (2007). Evolutionary Algorithms Refining a Heuristic: A Hybrid Method for Shared-Path Protections in WDM Networks Under SRLG Constraints. IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics). 37 (1), 51-61

Qingfu Zhang and Hui Li, (2007). MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition. IEEE Transactions on Evolutionary Computation. 11 (6), 712-731

Zhang, Q., Sun, J. and Tsang, E., (2007). Combinations of estimation of distribution algorithms and other techniques. International Journal of Automation and Computing. 4 (3), 273-280

Zhang, Q., Sun, J., Tsang, E. and Ford, J., (2006). Estimation of Distribution Algorithm with 2-opt Local Search for the Quadratic Assignment Problem. Studies in Fuzziness and Soft Computing. 192, 281-292

SUN, J., ZHANG, Q. and TSANG, E., (2005). DE/EDA: A new evolutionary algorithm for global optimization. Information Sciences. 169 (3-4), 249-262

Zhang, Q., Sun, J. and Tsang, E., (2005). An Evolutionary Algorithm With Guided Mutation for the Maximum Clique Problem. IEEE Transactions on Evolutionary Computation. 9 (2), 192-200

Zhang, Q., (2004). On Stability of Fixed Points of Limit Models of Univariate Marginal Distribution Algorithm and Factorized Distribution Algorithm. IEEE Transactions on Evolutionary Computation. 8 (1), 80-93

Zhang, Q., (2004). On the convergence of a factorized distribution algorithm with truncation selection. Complexity. 9 (4), 17-23

Zhang, Q. and Muhlenbein, H., (2004). On the Convergence of a Class of Estimation of Distribution Algorithms. IEEE Transactions on Evolutionary Computation. 8 (2), 127-136

Zhang, Q., Sun, J., Tsang, E. and Ford, J., (2004). Hybrid estimation of distribution algorithm for global optimization. Engineering Computations. 21 (1), 91-107

Zhang, Q., (2003). On the discrete-time dynamics of a PCA learning algorithm. Neurocomputing. 55 (3-4), 761-769

Jones, B., (2001). Preface. Statistics in Medicine. 20 (17-18), 2535-2535

Zhang, Q. and Yiu-Wung Leung, (2000). A class of learning algorithms for principal component analysis and minor component analysis. IEEE Transactions on Neural Networks. 11 (2), 529-533

Qingfu Zhang and Yiu Wing Leung, (2000). A class of learning algorithms for principal component analysis and minor component analysis. IEEE Transactions on Neural Networks. 11 (1), 200-204

Qingfu Zhang and Yiu-Wing Leung, (1999). An orthogonal genetic algorithm for multimedia multicast routing. IEEE Transactions on Evolutionary Computation. 3 (1), 53-62

Qingfu Zhang and Yiu-Wing Leung, (1998). Convergence of a Hebbian-type learning algorithm. IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing. 45 (12), 1599-1601

Zhang, Q. and Leung, Y-W., (1997). Dynamic system for solving complex eigenvalue problems. IEE Proceedings - Control Theory and Applications. 144 (5), 455-458

Zhang, Q. and Bao, Z., (1996). Neural network approach for linear absolute value problems. Tien Tzu Hsueh Pao/Acta Electronica Sinica. 24 (1), 97-100

Qingfu Zhang and Yiu-Wing Leung, (1995). Energy function for the one-unit Oja algorithm. IEEE Transactions on Neural Networks. 6 (5), 1291-1293

Zhang, Q. and Bao, Z., (1995). L -norm neural network model for TLS problems. International Journal of Engineering Intelligent Systems for Electrical Engineering and Communications. 3 (1), 61-64

Bingfu Zhang and Zheng Bao, (1995). Dynamical system for computing the eigenvectors associated with the largest eigenvalue of a positive definite matrix. IEEE Transactions on Neural Networks. 6 (3), 790-791

Conferences (110)

Shi, J., Sun, J. and Zhang, Q., (2019). Multi-objective Techniques for Single-Objective Local Search: A Case Study on Traveling Salesman Problem

Li, H., Sun, J., Zhang, Q. and Shui, Y., (2019). Adjustment of Weight Vectors of Penalty-Based Boundary Intersection Method in MOEA/D

Li, K. and Zhang, Q., (2019). Decomposition multi-objective optimisation

Han, Z., Liu, F., Xu, C., Zhang, K. and Zhang, Q., (2019). Efficient Multi-Objective Evolutionary Algorithm for Constrained Global Optimization of Expensive Functions

Li, G., Zhang, Q., Sun, J. and Han, Z., (2019). Radial Basis Function Assisted Optimization Method with Batch Infill Sampling Criterion for Expensive Optimization

Li, Z., Deng, J., Gao, W., Zhang, Q. and Liu, H-L., (2019). An Efficient Elitist Covariance Matrix Adaptation for Continuous Local Search in High Dimension

Zhu, Q., Zhang, Q., Lin, Q. and Sun, J., (2019). MOEA/D with Two Types of Weight Vectors for Handling Constraints

Derbel, B., Liefooghe, A., Zhang, Q., Verel, S., Aguirre, H. and Tanaka, K., (2018). A set-oriented MOEA/D

Shi, J., Zhang, Q., Derbel, B., Liefooghe, A. and Sun, J., (2018). Parallel pareto local search revisited

Li, K. and Zhang, Q., (2018). Decomposition multi-objective optimisation

Li, G., Zhang, Q. and Gao, W., (2018). Multipopulation evolution framework for multifactorial optimization

Sun, J., Zhang, H., Zhang, Q. and Chen, H., (2018). Balancing exploration and exploitation in multiobjective evolutionary optimization

(2018). Bio-inspired Computing: Theories and Applications

Shi, J., Zhang, Q., Derbel, B., Liefooghe, A. and Verel, S., (2017). Using Parallel Strategies to Speed up Pareto Local Search

Deng, J., Zhang, Q. and Li, H., (2017). On the Use of Dynamic Reference Points in HypE

Zhenhua Li and Qingfu Zhang, (2017). An efficient rank-1 update for Cholesky CMA-ES using auxiliary evolution path

Jialong Shi, Qingfu Zhang, Derbel, B. and Liefooghe, A., (2017). A Parallel Tabu Search for the Unconstrained Binary Quadratic Programming problem

Bhattacharjee, KS., Singh, HK., Ray, T. and Zhang, Q., (2017). Decomposition Based Evolutionary Algorithm with a Dual Set of reference vectors

Xi Lin, Zhang, Q. and Sam Kwong, (2017). An efficient batch expensive multi-objective evolutionary algorithm based on Decomposition

Wu, M., Kwong, S., Jia, Y., Li, K. and Zhang, Q., (2017). Adaptive weights generation for decomposition-based multi-objective optimization using Gaussian process regression

(2017). Preface

Chen, Q., Long, B. and Zhang, Q., (2016). Black-box expensive multiobjective optimization with adaptive in-fill rules

Zhou, Y., Kwong, S., Zhang, Q. and Wu, M., (2016). Adaptive patch-based sparsity estimation for image via MOEA/D

Li, H., Fan, Y., Zhang, Q., Xu, Z. and Deng, J., (2016). A multi-phase multiobjective approach based on decomposition for sparse reconstruction

Liu, H-L., Chen, L., Zhang, Q. and Deb, K., (2016). An evolutionary many-objective optimisation algorithm with adaptive region decomposition

Lyu, Y., Zhang, Q. and Wong, K-C., (2016). A cone order sequence based multi-objective evolutionary algorithm

Liu, B., Sun, N., Zhang, Q., Grout, V. and Gielen, G., (2016). A surrogate model assisted evolutionary algorithm for computationally expensive design optimization problems with discrete variables

Lin, X., Zhang, Q. and Kwong, S., (2016). A decomposition based multiobjective evolutionary algorithm with classification

Liu, B., Zhang, Q. and Gielen, G., (2016). A Surrogate-Model-Assisted Evolutionary Algorithm for Computationally Expensive Design Optimization Problems with Inequality Constraints

Li, Z. and Zhang, Q., (2016). What Does the Evolution Path Learn in CMA-ES?

Derbel, B., Liefooghe, A., Zhang, Q., Aguirre, H. and Tanaka, K., (2016). Multi-objective Local Search Based on Decomposition

Derbel, B., Liefooghe, A., Zhang, Q., Aguirre, H. and Tanaka, K., (2016). Local Search Move Strategies within MOEA/D

Wang, R., Zhang, Q. and Zhang, T., (2015). Pareto Adaptive Scalarising Functions for Decomposition Based Algorithms

Wang, Z., Zhang, Q. and Li, H., (2015). Balancing Convergence and Diversity by Using Two Different Reproduction Operators in MOEA/D: Some Preliminary Work

Wu, M., Kwong, S., Zhang, Q., Li, K., Wang, R. and Liu, B., (2015). Two-Level Stable Matching-Based Selection in MOEA/D

Chen, Q., Fu, C. and Zhang, Q., (2015). On performance of decomposition-based MOEAs in noisy environment

Li, H., Ding, M., Deng, J. and Zhang, Q., (2015). On the use of random weights in MOEA/D

Li, K., Deb, K. and Zhang, Q., (2015). Evolutionary multiobjective optimization with hybrid selection principles

Zhang, X., Zhou, Y., Zhang, Q., Lee, VCS. and Li, M., (2015). Multi-objective Optimization of Barrier Coverage with Wireless Sensors

Wang, Z., Zhang, Q., Gong, M. and Zhou, A., (2014). A replacement strategy for balancing convergence and diversity in MOEA/D

Alhindi, A. and Zhang, Q., (2014). MOEA/D with Tabu Search for multiobjective permutation flow shop scheduling problems

Li, Y., Cai, X., Fan, Z. and Zhang, Q., (2014). An external archive guided multiobjective evolutionary approach based on decomposition for continuous optimization

Alhindi, A., Zhang, Q. and Tsang, E., (2014). Hybridisation of decomposition and GRASP for combinatorial multiobjective optimisation

Li, H., Zhang, Q. and Deng, J., (2014). Multiobjective test problems with complicated Pareto fronts: Difficulties in degeneracy

Liu, B., Chen, Q., Zhang, Q., Gielen, G. and Grout, V., (2014). Behavioral study of the surrogate model-aware evolutionary search framework

Ke, L., Guo, H. and Zhang, Q., (2014). A cooperative approach between metaheuristic and branch-and-price for the team orienteering problem with time windows

Zhou, A., Zhang, Q. and Zhang, G., (2013). Approximation Model Guided Selection for Evolutionary Multiobjective Optimization

Rubio-Largo, A., Zhang, Q. and Vega-Rodriguez, MA., (2013). MOEA/D for traffic grooming in WDM optical networks

Alhindi, A. and Zhang, Q., (2013). MOEA/D with guided local search: Some preliminary experimental results

Peng, W. and Zhang, Q., (2012). Network Topology Planning Using MOEA/D with Objective-Guided Operators

Li, H., Su, X., Xu, Z. and Zhang, Q., (2012). MOEA/D with Iterative Thresholding Algorithm for Sparse Optimization Problems

Liu, B., Qingfu Zhang, Fernandez, FV. and Gielen, G., (2012). Self-adaptive lower confidence bound: A new general and effective prescreening method for Gaussian Process surrogate model assisted evolutionary algorithms

Zhou, A., Zhang, Q. and Guixu Zhang, (2012). A multiobjective evolutionary algorithm based on decomposition and probability model

Echegoyen, C., Zhang, Q., Mendiburu, A., Santana, R. and Lozano, JA., (2011). On the limits of effectiveness in estimation of distribution algorithms

Ma, J., Wang, Y., Gong, M., Jiao, L. and Zhang, Q., (2011). Spatio-temporal data evolutionary clustering based on MOEA/D

Saxena, DK., Zhang, Q., Duro, JA. and Tiwari, A., (2011). Framework for Many-Objective Test Problems with Both Simple and Complicated Pareto-Set Shapes

Gong, M., Liu, F., Zhang, W., Jiao, L. and Zhang, Q., (2011). Interactive MOEA/D for multi-objective decision making

Tairan, N. and Zhang, Q., (2011). P-GLS-II

Durillo, JJ., Zhang, Q., Nebro, AJ. and Alba, E., (2011). Distribution of Computational Effort in Parallel MOEA/D

Zhou, A. and Zhang, Q., (2010). A surrogate-assisted evolutionary algorithm for minimax optimization

Konstantinidis, A., Charalambous, C., Zhou, A. and Zhang, Q., (2010). Multi-objective mobile agent-based Sensor Network Routing using MOEA/D

Tairan, N. and Zhang, Q., (2010). Population-Based Guided Local Search: Some preliminary experimental results

Jan, MA. and Zhang, Q., (2010). MOEA/D for constrained multiobjective optimization: Some preliminary experimental results

Liu, B., Fernandez, FV., Zhang, Q., Pak, M., Sipahi, S. and Gielen, G., (2010). An enhanced MOEA/D-DE and its application to multiobjective analog cell sizing

Khan, W. and Zhang, Q., (2010). MOEA/D-DRA with two crossover operators

Zhang, Q., Li, H., Maringer, D. and Tsang, E., (2010). MOEA/D with NBI-style Tchebycheff approach for portfolio management

Hasan, BAS., Gan, JQ. and Zhang, Q., (2010). Multi-objective evolutionary methods for channel selection in Brain-Computer Interfaces: Some preliminary experimental results

Konstantinidis, A., Yang, K. and Zhang, QT., (2009). Problem-Specific Encoding and Genetic Operation for a Multi-Objective Deployment and Power Assignment Problem in Wireless Sensor Networks

Konstantinidis, A., Yang, K., Zhang, Q. and Gordejuela-Sanchez, F., (2009). Multiobjective K-Connected Deployment and Power Assignment in WSNs Using Constraint Handling

Chen, SH., Chang, PC. and Zhang, Q., (2009). A self-guided genetic algorithm for flowshop scheduling problems

Chen, SH., Chang, PC., Zhang, Q. and Wang, CB., (2009). A guided memetic algorithm with probabilistic models

Brownlee, AEI., McCall, JAW., Shakya, SK. and Zhang, Q., (2009). Structure learning and optimisation in a Markov-network based estimation of distribution algorithm

Chih-Ming Chen, Ying-ping Chen and Qingfu Zhang, (2009). Enhancing MOEA/D with guided mutation and priority update for multi-objective optimization

Zhang, Q., Liu, W. and Li, H., (2009). The performance of a new version of MOEA/D on CEC09 unconstrained MOP test instances

Sun, Y., Sun, J. and Zhang, Q., (2009). An Evolutionary Approach for Survivable Network under SRLG Constraints

Liu, W., Zhang, Q., Tsang, E. and Virginas, B., (2009). Fuzzy clustering based Gaussian Process Model for large training set and its application in expensive evolutionary optimization

Konstantinidis, A., Zhang, Q. and Yang, K., (2009). A Subproblem-dependent Heuristic in MOEA/D for the Deployment and Power Assignment Problem in Wireless Sensor Networks

Konstantinidis, A., Yang, K. and Zhang, Q., (2008). An Evolutionary Algorithm to a Multi-Objective Deployment and Power Assignment Problem in Wireless Sensor Networks

Chen, S-H., Chang, P-C. and Zhang, Q., (2008). Self-Guided Genetic Algorithm

Wei Peng and Zhang, Q., (2008). A decomposition-based multi-objective Particle Swarm Optimization algorithm for continuous optimization problems

Chang, PC., Chen, SH., Zhang, Q. and Lin, JL., (2008). MOEA/D for flowshop scheduling problems

Brownlee, AEI., McCall, JAW., Qingfu Zhang and Brown, DF., (2008). Approaches to selection and their effect on fitness modelling in an Estimation of Distribution Algorithm

Zhou, A., Zhang, Q., Jin, Y. and Sendhoff, B., (2008). Combination of EDA and DE for continuous biobjective optimization

Wudong Liu, Qingfu Zhang, Tsang, E. and Virginas, B., (2008). Tchebycheff approximation in Gaussian Process model composition for multi-objective expensive black box

Aimin Zhou, Qingfu Zhang, Yaochu Jin and Sendhoff, B., (2007). Adaptive modelling strategy for continuous multi-objective optimization

Zhou, A., Jin, Y., Zhang, Q., Sendhoff, B. and Tsang, E., (2007). Prediction-based population re-initialization for evolutionary dynamic multi-objective optimization

Zhou, A., Zhang, Q., Jin, Y., Sendhoff, B. and Tsang, E., (2007). Global multiobjective optimization via estimation of distribution algorithm with biased initialization and crossover

Liu, W., Zhang, Q., Tsang, E., Liu, C. and Virginas, B., (2007). On the performance of metamodel assisted MOEA/D

Salhi, A., Rodríguez, JAV. and Zhang, Q., (2007). An estimation of distribution algorithm with guided mutation for a complex flow shop scheduling problem

(2007). Preface

Ren, Y., Wang, J., Zhang, Y. and Fang, L., (2007). Identity-Based Key Issuing Protocol for Ad Hoc Networks

Wang, Y., Zhang, Q. and Wang, PS., (2007). Proceedings of the IEEE International Conference on Micro Electro Mechanical Systems (MEMS): Preface

Li, H. and Zhang, Q., (2006). A Multiobjective Differential Evolution Based on Decomposition for Multiobjective Optimization with Variable Linkages

Li, H. and Zhang, Q., (2006). A Decomposition-based evolutionary strategy for Bi-objective LOTZ problem

Zhang, Q. and Sun, J., (2006). Iterated local search with guided mutation

Zhou, A., Zhang, Q., Jin, Y., Sendhoff, B. and Tsang, E., (2006). Modelling the Population Distribution in Multi-objective Optimization by Generative Topographic Mapping

Zhou, A., Jin, Y., Zhang, Q., Sendhoff, B. and Tsang, E., (2006). Combining model-based and genetics-based offspring generation for multi-objective optimization using a convergence criterion

Sun, J., Zhang, Q., Li, J. and Yao, X., (2006). A Hybrid Estimation of Distribution Algorithm for CDMA Cellular System Design

Tsirogiannis, E., Theodoropoulos, G., Chen, D., Zhang, Q., Janin, L. and Edwards, D., (2006). A Framework for Distributed Simulation of Asynchronous Handshake Circuits

Konstantinidis, A., Zhang, Q., Yang, K. and Henning, I., (2006). WSN19-5: Energy-aware Topology Control in Sensor Networks Using Modern Heuristics

Shumao Ou, Kun Yang and Qingfu Zhang, (2006). An efficient runtime offloading approach for pervasive services

Wang, X., Kwiatkowska, M., Theodoropoulos, G. and Zhang, Q., (2006). Opportunities and Challenges in Process-algebraic Verification of Asynchronous Circuit Designs

Zhou, A., Zhang, Q., Jin, Y., Tsang, E. and Okabe, T., (2005). A model-based evolutionary algorithm for Bi-objective optimization

Camacho, JH., Salhi, A. and Zhang, Q., (2005). A Graph Theoretic Approach to Key Equivalence

Wang, X., Kwiatkowska, M., Theodoropoulos, G. and Zhang, Q., (2005). Towards a Unifying CSP approach to Hierarchical Verification of Asynchronous Hardware

He, J., Yao, X. and Zhang, Q., (2004). To understand one-dimensional continuous fitness landscapes by drift analysis

Li, H., Zhang, Q., Tsang, E. and Ford, JA., (2004). Hybrid Estimation of Distribution Algorithm for Multiobjective Knapsack Problem

Qingfu Zhang, Allinson, NM. and Hujun Yin, (2000). Population optimization algorithm based on ICA

Zhang, Q., Yin, H. and Allinson, NM., (2000). Simplified ICA based denoising method

Wu, S., Zhang, Q. and Chen, H., (1996). New evolutionary model based on family eugenics: the first results

Contact

qzhang@essex.ac.uk

Location:

Colchester Campus