Overview

This webpage is significantly incomplete. All information related to my research and opennings in my group are in my personal homepage.

I am keen on looking for talented people (including PhD students and Postdocs) to join my lab. At the moment, I am interested in the following topics:

1. Data-driven optimization (e.g., Bayesian optimization and reinforcement learning) for complex optimization tasks.
2. Search-based software engineering, e.g., software defect prediction, configurable software system, code naturalness and automatic bug repair.
3. Artificial intelligence for scientific discovery, e.g., new material discovery and RNA structure prediction.

Please refer to my homepage for more inforamtion of my research and potential opportunities in my lab.

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Publications

_{Copyright Notice: Any articles made available for download are for personal use only. Any other use requires prior permission of the author and the copyright holder.}

| To Appear | 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012 | 2011 | 2010 | 2009 |

To Appear

• Zou J, Ji C, Yang S, Zhang Y, Zheng J, Li K. A knee-point-based evolutionary algorithm using weighted subpopulation for many-objective optimization, Swarm and Evolutionary Computation, DOI:10.1016/j.swevo.2019.02.001.
• Wu M, Li K, Kwong S, Zhang Q, Zhang J. Learning to Decompose: A Paradigm for Decomposition-Based Multi-Objective Optimization, IEEE Transactions on Evolutionary Computation, DOI:10.1109/TEVC.2018.2865931.
• Li K, Chen R, Min G, Yao X. Integration of Preferences in Decomposition Multi-Objective Optimization, IEEE Transactions on Cybernetics, DOI:10.1109/TCYB.2018.2859363.
• Wu M, Li K, Kwong S, Zhang Q. Evolutionary Many-Objective Optimization Based on Adversarial Decomposition, IEEE Transactions on Cybernetics.
• Cheng R, Li M, Li K, Yao X. Evolutionary Multiobjective Optimization Based Multimodal Optimization: Fitness Landscape Approximation and Peak Detection, IEEE Transactions on Evolutionary Computation, DOI:10.1109/TEVC.2017.2744328.

2024

• Li K, Li F. (2024) Multi-Fidelity Methods for Optimization: A Survey. [PDF]
• Li K, Guo H. (2024) Human-in-the-Loop Policy Optimization for Preference-Based Multi-Objective Reinforcement Learning. [PDF]
• Li S, Li K, Li W, Yang M. (2024) Evolutionary Alternating Direction Method of Multipliers for Constrained Multi-Objective Optimization with Unknown Constraints. [PDF]
• Li K, Chen R, Yao X. (2024) A Data-Driven Evolutionary Transfer Optimization for Expensive Problems in Dynamic Environments, IEEE Transactions on Evolutionary Computation, pages 1-1, DOI:10.1109/tevc.2023.3307244. [PDF]

2023

• Yang H, Zhang C, Li K. (2023) PyABSA: A Modularized Framework for Reproducible Aspect-based Sentiment Analysis, International Conference on Information and Knowledge Management, Proceedings, pages 5117-5122, DOI:10.1145/3583780.3614752.
• Tanabe R, Li K. (2023) Quality Indicators for Preference-Based Evolutionary Multi-Objective Optimization Using a Reference Point: A Review and Analysis, IEEE Transactions on Evolutionary Computation, DOI:10.1109/TEVC.2023.3319009.
• Williams P, Li K, Min G. (2023) A Surrogate Assisted Evolutionary Strategy for Image Approximation by Density-Ratio Estimation, 2023 IEEE Congress on Evolutionary Computation, CEC 2023, DOI:10.1109/CEC53210.2023.10254060.
• Williams PN, Li K. (2023) Black-Box Sparse Adversarial Attack via Multi-Objective Optimisation CVPR Proceedings, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), DOI:10.1109/cvpr52729.2023.01183.
• Li K, Lai G, Yao X. (2023) Interactive Evolutionary Multiobjective Optimization via Learning to Rank, IEEE Transactions on Evolutionary Computation, volume 27, no. 4, pages 749-763, DOI:10.1109/tevc.2023.3234269. [PDF]
• Chen R, Li K. (2023) Data-Driven Evolutionary Multi-objective Optimization Based on Multiple-Gradient Descent for Disconnected Pareto Fronts, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 13970 LNCS, pages 56-70, DOI:10.1007/978-3-031-27250-9_5.
• Zou J, Sun R, Liu Y, Hu Y, Yang S, Zheng J, Li K. (2023) A Multipopulation Evolutionary Algorithm Using New Cooperative Mechanism for Solving Multiobjective Problems With Multiconstraint, IEEE Transactions on Evolutionary Computation, volume 28, no. 1, pages 267-280, DOI:10.1109/TEVC.2023.3260306.
• Williams P, Li K, Min G. (2023) Sparse Adversarial Attack via Bi-objective Optimization, Evolutionary Multi-Criterion Optimization, Springer Nature, 118-133, DOI:10.1007/978-3-031-27250-9_9.
• Guan Y, Song Q, Qi W, Li K, Guo L, Jamalipour A. (2023) Multidimensional Resource Fragmentation-Aware Virtual Network Embedding in MEC Systems Interconnected by Metro Optical Networks. [PDF]
• Chen L, Liu HL, Li K, Tan KC. (2023) Evolutionary Bi-level Optimization via Multi-objective Transformation-Based Lower Level Search, IEEE Transactions on Evolutionary Computation, DOI:10.1109/TEVC.2023.3236455.
• Lyu B, Lu L, Hamdi M, Wen S, Yang Y, Li K. (2023) MTLP-JR: Multi-task learning-based prediction for joint ranking in neural architecture search, Computers and Electrical Engineering, volume 105, DOI:10.1016/j.compeleceng.2022.108474.
• Lyu B, Hamdi M, Yang Y, Cao Y, Yan Z, Li K, Wen S, Huang T. (2023) Efficient Spectral Graph Convolutional Network Deployment on Memristive Crossbars, IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE, volume 7, no. 2, pages 415-425, DOI:10.1109/TETCI.2022.3210998. [PDF]
• Li K, Chen R. (2023) Batched Data-Driven Evolutionary Multiobjective Optimization Based on Manifold Interpolation, IEEE Transactions on Evolutionary Computation, volume 27, no. 1, pages 126-140, DOI:10.1109/TEVC.2022.3162993.
• Lyu B, Yang Y, Wen S, Huang T, Li K. (2023) Neural Architecture Search for Portrait Parsing, IEEE Transactions on Neural Networks and Learning Systems, volume 34, no. 3, pages 1112-1121, DOI:10.1109/TNNLS.2021.3104872.

2022

• Li K, Chen R, Yao X. (2022) A Data-Driven Evolutionary Transfer Optimization for Expensive Problems in Dynamic Environments. [PDF]
• Li S, Li K, Li W. (2022) Do We Really Need to Use Constraint Violation in Constrained Evolutionary Multi-objective Optimization?, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 13399 LNCS, pages 124-137, DOI:10.1007/978-3-031-14721-0_9.
• Zhou S, Li K, Min G. (2022) Attention-Based Genetic Algorithm for Adversarial Attack in Natural Language Processing, Parallel Problem Solving from Nature – PPSN XVII, Springer Nature, 341-355, DOI:10.1007/978-3-031-14714-2_24.
• Zhou S, Li K, Min G. (2022) Adversarial example generation via genetic algorithm, Proceedings of the Genetic and Evolutionary Computation Conference Companion, DOI:10.1145/3520304.3528981.
• Li K, Yang H, Visser W. (2022) Evolutionary Multi-Task Injection Testing on Web Application Firewalls. [PDF]
• Li S, Li K, Li W. (2022) Do We Really Need to Use Constraint Violation in Constrained Evolutionary Multi-Objective Optimization?. [PDF]
• Chen R, Li K. (2022) Data-Driven Evolutionary Multi-Objective Optimization Based on Multiple-Gradient Descent for Disconnected Pareto Fronts. [PDF]
• Li K, Lai G, Yao X. (2022) Interactive Evolutionary Multi-Objective Optimization via Learning-to-Rank. [PDF]
• Xu J, Li K. (2022) Automated Few-Shot Time Series Forecasting based on Bi-level Programming. [PDF]
• Williams P, Li K. (2022) Art-Attack: Black-Box Adversarial Attack via Evolutionary Art. [PDF]
• Wu J, Luo C, Luo Y, Li K. (2022) Distributed UAV Swarm Formation and Collision Avoidance Strategies Over Fixed and Switching Topologies, IEEE Transactions on Cybernetics, volume 52, no. 10, pages 10969-10979, DOI:10.1109/tcyb.2021.3132587.
• Huang M, Mao P, Li K. (2022) Unlocking the Secrets of Software Configuration Landscapes-Ruggedness, Accessibility, Escapability, and Transferability. [PDF]
• Li K, Nie H, Gao H, Yao X. (2022) Posterior Decision Making Based on Decomposition-Driven Knee Point Identification, IEEE Transactions on Evolutionary Computation, volume 26, no. 6, pages 1409-1423, DOI:10.1109/TEVC.2021.3116121.
• Chen L, Liu HL, Tan KC, Li K. (2022) Transfer Learning-Based Parallel Evolutionary Algorithm Framework for Bilevel Optimization, IEEE Transactions on Evolutionary Computation, volume 26, no. 1, pages 115-129, DOI:10.1109/TEVC.2021.3095313.

2021

• Yuce S, Li K. (2021) An Enhancement of the NSGA-II Reliability Optimization Using Extended Kalman Filter Based Initialization, Advances in Intelligent Systems and Computing, Springer International Publishing, 121-128, DOI:10.1007/978-3-030-87094-2_11. [PDF]
• Li K, Chen R. (2021) Batched Data-Driven Evolutionary Multi-Objective Optimization Based on Manifold Interpolation. [PDF]
• Li K. (2021) Decomposition Multi-Objective Evolutionary Optimization: From State-of-the-Art to Future Opportunities. [PDF]
• Billingsley J, Li K, Min G, Georgalas N. (2021) Evolutionary Multi-Objective Virtual Network Function Placement: A Formal Model and Effective Algorithms. [PDF]
• Billingsley J, Li K, Miao W, Min G, Georgalas N. (2021) Parallel Algorithms for the Multiobjective Virtual Network Function Placement Problem, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 12654 LNCS, pages 708-720, DOI:10.1007/978-3-030-72062-9_56.
• Xu J, Li K, Abusara M. (2021) Multi-Objective Reinforcement Learning based Multi-Microgrid System Optimisation Problem. [PDF]
• Shan X, Li K. (2021) An Improved Two-Archive Evolutionary Algorithm for Constrained Multi-Objective Optimization. [PDF]

2020

• Billingsley J, Li K, Miao W, Min G, Georgalas N. (2020) Routing-Led Placement of VNFs in Arbitrary Networks, 2020 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC). [PDF]
• Li K, Xiang Z, Chen T, Tan KC. (2020) BiLO-CPDP: Bi-Level Programming for Automated Model Discovery in Cross-Project Defect Prediction. [PDF]
• Liu M, Li K, Chen T. (2020) DeepSQLi: Deep Semantic Learning for Testing SQL Injection. [PDF]
• Li K, Nie H, Gao H, Yao X. (2020) Knee Point Identification Based on Trade-Off Utility. [PDF]
• Sun L, Li K. (2020) Adaptive Operator Selection Based on Dynamic Thompson Sampling for MOEA/D. [PDF]
• Ruan X, Li K, Derbel B, Liefooghe A. (2020) Surrogate Assisted Evolutionary Algorithm for Medium Scale Expensive Multi-Objective Optimisation Problems. [PDF]
• Li K, Xiang Z, Chen T, Wang S, Tan KC. (2020) Understanding the Automated Parameter Optimization on Transfer Learning for CPDP: An Empirical Study. [PDF]
• Billingsley J, Li K, Miao W, Min G, Georgalas N. (2020) Routing-Led Placement of VNFs in Arbitrary Networks. [PDF]

2019

• Li K, Liao M, Deb K, Min G, Yao X. (2019) Does Preference Always Help? A Holistic Study on Preference-Based Evolutionary Multi-Objective Optimisation Using Reference Points. [PDF]
• Liu M, Li K, Chen T. (2019) Security testing of web applications: A search-based approach for detecting SQL injection vulnerabilities, GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion, pages 417-418, DOI:10.1145/3319619.3322026.
• Li K, Zhang Q. (2019) Decomposition multi-objective optimisation current developments and future opportunities, GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion, pages 1002-1031, DOI:10.1145/3319619.3323369.
• Wang R, Ye S, Li K, Kwong S. (2019) Bayesian Network Based Label Correlation Analysis For Multi-label Classifier Chain. [PDF]
• Li K. (2019) Progressive preference learning: Proof-of-principle results in MOEA/D, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 11411 LNCS, pages 631-643, DOI:10.1007/978-3-030-12598-1_50.
• Billingsley J, Li K, Miao W, Min G, Georgalas N. (2019) A formal model for multi-objective optimisation of network function virtualisation placement, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 11411 LNCS, pages 529-540, DOI:10.1007/978-3-030-12598-1_42.
• Billingsley J, Li K, Miao W, Min G, Georgalas N. (2019) A Formal Model for Multi-objective Optimisation of Network Function Virtualisation Placement, The 10th International Conference on Evolutionary Multi-Criterion Optimization, East Lansing, Michigan, Usa, 10th - 13th Mar 2019, DOI:10.1007/978-3-030-12598-1\_42.
• Li K. (2019) Progressive Preference Learning: Proof-of-Principle Results in MOEA/D, The 10th International Conference on Evolutionary Multi-Criterion Optimization, East Lansing, Michigan, Usa, 10th - 13th Mar 2019, DOI:10.1007/978-3-030-12598-1\_50.
• Li W, Li K, Guo D, Min G, Qi H, Zhang J. (2019) Cost-Minimizing Bandwidth Guarantee for Inter-Datacenter Traffic, IEEE Transactions on Cloud Computing, volume 7, no. 2, pages 483-494, DOI:10.1109/tcc.2016.2629506. [PDF]

2018

• Kumar S, Bahsoon R, Chen T, Li K, Buyya R. (2018) Multi-Tenant Cloud Service Composition using Evolutionary Optimization, 2018 IEEE 24TH INTERNATIONAL CONFERENCE ON PARALLEL AND DISTRIBUTED SYSTEMS (ICPADS 2018), pages 972-979, DOI:10.1109/ICPADS.2018.00129. [PDF]
• Kumar S, Bahsoon R, Chen T, Li K, Buyya R. (2018) Multi-Tenant Cloud Service Composition Using Evolutionary Optimization, Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS, volume 2018-December, pages 972-979, DOI:10.1109/PADSW.2018.8644640.
• Li K, Zhang Q. (2018) Decomposition multi-objective optimisation: Current developments and future opportunities, GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion, pages 907-936, DOI:10.1145/3205651.3207856.
• Li K, Chen R, Savic D, Yao X. (2018) Interactive Decomposition Multi-Objective Optimisation via Progressively Learned Value Functions, IEEE Transactions on Fuzzy Systems, volume 27, pages 849-860, DOI:10.1109/TFUZZ.2018.2880700. [PDF]
• Chen T, Li K, Bahsoon R, Yao X. (2018) FEMOSAA: Feature Guided and Knee Driven Multi-Objective Optimization for Self-Adaptive Software, ACM Transactions on Software Engineering and Methodology, volume 27, pages 1-50, DOI:10.1145/3204459.
• Li K, Chen R, Fu G, Yao X. (2018) Two-Archive Evolutionary Algorithm for Constrained Multi-Objective Optimization, IEEE Transactions on Evolutionary Computation, volume 23, pages 303-315, DOI:10.1109/TEVC.2018.2855411. [PDF]
• Li K, Chen R, Yao X. (2018) Dynamic Multi-Objectives Optimization with a Changing Number of Objectives, IEEE Transactions on Evolutionary Computation, volume 22, no. 1, pages 157-171, DOI:10.1109/TEVC.2017.2669638.

2017

• Li K, Deb K, Yao X. (2017) R-Metric: Evaluating the Performance of Preference-Based Evolutionary Multi-Objective Optimization Using Reference Points, IEEE Transactions on Evolutionary Computation, DOI:10.1109/TEVC.2017.2737781.
• Xie H, Wang FL, Mao X, Li K, Li Q, Wang H. (2017) Recent advances in semantic computing and personalization, Neurocomputing, volume 254, pages 1339-1351, DOI:10.1016/j.neucom.2017.02.073.
• Wu M, Kwong S, Jia Y, Li K, Zhang Q. (2017) Adaptive Weights Generation for Decomposition-Based Multi-Objective Optimization Using Gaussian Process Regression, the 18th Annual Conference on Genetic and Evolutionary Computation (GECCO 2017), Berlin, Germany, 15th - 19th Jul 2017, DOI:10.1145/3071178.3071339.
• Wu M, Li K, Kwong S, Zhou Y, Zhang Q. (2017) Matching-Based Selection with Incomplete Lists for Decomposition Multi-Objective Optimization, IEEE Transactions on Evolutionary Computation, volume 21, pages 554-568, DOI:10.1109/TEVC.2017.2656922.
• Li K, Deb K, Altinoz T, Yao X. (2017) Empirical Investigations of Reference Point Based Methods When Facing a Massively Large Number of Objectives: First Results, 9th International Conference on Evolutionary Multi-Criterion Optimization, Münster, Germany, 19th - 22nd Mar 2017, DOI:10.1007/978-3-319-54157-0_27.
• Li K, Deb K, Zhang Q, Zhang Q. (2017) Efficient Nondomination Level Update Method for Steady-State Evolutionary Multiobjective Optimization, IEEE Transactions on Cybernetics, volume 47, no. 9, pages 2838-2849, DOI:10.1109/TCYB.2016.2621008.

2016

• Li K, Omidvar M, Deb K, Yao X. (2016) Variable Interaction in Multi-objective Optimization Problems, 14th International Conference on Parallel Problem Solving from Nature – PPSN XIV, Edinburgh, Uk, 17th - 21st Sep 2016, DOI:10.1007/978-3-319-45823-6_37.
• Xie H, Li X, Wang T, Chen L, Li K, Wang FL, Cai Y, Li Q, Min H. (2016) Personalized search for social media via dominating verbal context, Neurocomputing, volume 172, pages 27-37, DOI:10.1016/j.neucom.2014.12.109. [PDF]

2015

• Li K, Deb K, Zhang Q. (2015) Evolutionary multiobjective optimization with hybrid selection principles, 2015 IEEE Congress on Evolutionary Computation -- CEC'15, Sendai, Japan, 25th - 28th May 2015, DOI:10.1109/CEC.2015.7256986.
• Wu M, Kwong S, Zhang Q, Li K, Wang R, Liu B. (2015) Two-Level Stable Matching-Based Selection in MOEA/D, 2015 IEEE International Conference on Systems, Mans and Cybernetics -- SMC'15, Hong Kong, 9th - 12th Oct 2015, DOI:10.1109/SMC.2015.302.
• Cao J, Kwong S, Wang R, Li X, Li K, Kong X. (2015) Class-specific soft voting based multiple extreme learning machines ensemble, Neurocomputing, volume 149, pages 275-284, DOI:10.1016/j.neucom.2014.02.072. [PDF]
• Li K, Kwong S, Deb K. (2015) A dual-population paradigm for evolutionary multiobjective optimization, Information Sciences, volume 309, pages 50-72, DOI:10.1016/j.ins.2015.03.002. [PDF]
• Li K, Deb K, Zhang Q, Kwong S. (2015) An Evolutionary Many-Objective Optimization Algorithm Based on Dominance and Decomposition, IEEE Transactions on Evolutionary Computation, volume 19, no. 5, pages 694-716, DOI:10.1109/tevc.2014.2373386. [PDF]
• Li K, Kwong S, Zhang Q, Deb K. (2015) Interrelationship-Based Selection for Decomposition Multiobjective Optimization, IEEE Transactions on Cybernetics, volume 45, no. 10, pages 2076-2088, DOI:10.1109/tcyb.2014.2365354. [PDF]

2014

• Cao J-J, Kwong S, Wang R, Li K. (2014) AN INDICATOR-BASED SELECTION MULTI-OBJECTIVE EVOLUTIONARY ALGORITHM WITH PREFERENCE FOR MULTI-CLASS ENSEMBLE, PROCEEDINGS OF 2014 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS (ICMLC), VOL 1, pages 147-152. [PDF]
• Li K, Kwong S. (2014) A general framework for evolutionary multiobjective optimization via manifold learning, Neurocomputing, volume 146, pages 65-74, DOI:10.1016/j.neucom.2014.03.070. [PDF]
• Li M, Yang S, Li K, Liu X. (2014) Evolutionary Algorithms With Segment-Based Search for Multiobjective Optimization Problems, IEEE Transactions on Cybernetics, volume 44, no. 8, pages 1295-1313, DOI:10.1109/tcyb.2013.2282503. [PDF]
• Li K, Fialho A, Kwong S, Zhang Q. (2014) Adaptive Operator Selection With Bandits for a Multiobjective Evolutionary Algorithm Based on Decomposition, IEEE Transactions on Evolutionary Computation, volume 18, no. 1, pages 114-130, DOI:10.1109/tevc.2013.2239648. [PDF]
• Li K, Zhang Q, Kwong S, Li M, Wang R. (2014) Stable Matching-Based Selection in Evolutionary Multiobjective Optimization, IEEE Transactions on Evolutionary Computation, volume 18, no. 6, pages 909-923, DOI:10.1109/TEVC.2013.2293776. [PDF]

2013

• Li K, Wang R, Kwong S, Cao J. (2013) Evolving Extreme Learning Machine Paradigm with Adaptive Operator Selection and Parameter Control, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, volume 21, no. supp02, pages 143-154, DOI:10.1142/S0218488513400229.
• Li K, Kwong S, Wang R, Tang K-S, Man K-F. (2013) Learning paradigm based on jumping genes: A general framework for enhancing exploration in evolutionary multiobjective optimization, Information Sciences, volume 226, pages 1-22, DOI:10.1016/j.ins.2012.11.002. [PDF]

2012

• Cao J, Kwong S, Wang R, Li K. (2012) A weighted voting method using minimum square error based on Extreme Learning Machine, 2012 International Conference on Machine Learning and Cybernetics -- ICMLC'12, Xi'an, China, 15th - 17th Jul 2012, DOI:10.1109/ICMLC.2012.6358949.
• Li K, Kwong S, Wang R, Cao J, Rudas I. (2012) Multi-objective differential evolution with self-navigation, 2012 IEEE International Conference on Systems, Mans and Cybernetics -- SMC'12, Alaska, Usa, 14th - 17th Oct 2012, DOI:10.1109/ICSMC.2012.6377775.
• Li K, Kwong S, Cao J, Li M, Zheng J, Shen R. (2012) Achieving balance between proximity and diversity in multi-objective evolutionary algorithm, Information Sciences, volume 182, no. 1, pages 220-242, DOI:10.1016/j.ins.2011.08.027. [PDF]

2011

• Li K, Fialho A, Kwong S. (2011) Multi-Objective Differential Evolution with Adaptive Control of Parameters and Operators, 5th International Conference on Learning and Intelligent OptimizatioN -- LION 5, Rome, Italy, 17th - 21st Jan 2011, DOI:10.1007/978-3-642-25566-3_37.
• Li K, Kwong S, Man K. (2011) JGBL paradigm: A Novel Strategy to Enhance the Exploration Ability of NSGA-II, 2011 Annual Conference on Genetic and Evolutionary Computation -- GECCO'11, Dublin, Irland, 7th - 11th Jul 2011, DOI:10.1145/2001858.2001915.
• Cao J, Wang H, Kwong S, Li K. (2011) Combining interpretable fuzzy rule-based classifiers via multi-objective hierarchical evolutionary algorithm, 2011 IEEE International Conference on Systems, Mans and Cybernetics -- SMC'11, Anchorage, Usa, 9th - 12th Oct 2011, DOI:10.1109/ICSMC.2011.6083928.

2010

• Li K, Zheng J, Li M, Zhou C, Lv H. (2010) A Novel Slicing Based Algorithm to Calculate Hypervolume for Multi-Objective Optimization Problems, ICIC Express Letters: An International Journal of Research and Surveys, pages 1113-1120.
• Li M, Zheng J, Shen R, Li K, Yuan Q. (2010) A grid-based fitness strategy for evolutionary many-objective optimization, 2010 Annual conference on Genetic and evolutionary computation -- GECCO'10, Oregon, Usa, 7th - 11th Jul 2010, DOI:10.1145/1830483.1830570.
• Li M, Zheng J, Li K, Yuan Q, Shen R. (2010) Enhancing Diversity for Average Ranking Method in Evolutionary Many-Objective Optimization, 11th International Conference on Parallel Problem Solving from Nature -- PPSN XI, Kraków, Poland, 11th - 15th Sep 2010, DOI:10.1007/978-3-642-15844-5_65.

2009

• Li K, Zheng J, Zhou C, Lv H. (2009) An Improved Differential Evolution for Multi-objective Optimization, 2009 WRI World Congress on Computer Science and Information Engineering -- CSIE'09, Los Angeles, Usa, 31st Mar - 2nd Apr 2009, DOI:10.1109/CSIE.2009.181.
• Lv H, Zheng J, Wu J, Zhou C, Li K. (2009) The Convergence Analysis of Genetic Algorithm Based on Space Mating, 5th International Conference on Natural Computation -- ICNC'09, Tianjin, 14th - 16th Oct 2009, DOI:10.1109/ICNC.2009.39.
• Zhou C, Zheng J, Li K, Lv H. (2009) Objective Reduction based on the Least Square Method for Large-dimensional Multiobjective Optimization Problem, 5th International Conference on Natural Computation -- ICNC'09, Tianjin, 14th - 16th Oct 2009, DOI:10.1109/ICNC.2009.40.
• Li M, Zheng J, Li K, Wu J, Xiao G. (2009) An Spanning Tree based method for pruning non-dominated solutions in multi-objective optimization problems, 2009 IEEE International Conference on Systems, Mans and Cybernetics -- SMC'09, San Antonio, Usa, 11th - 14th Oct 2009, DOI:10.1109/ICSMC.2009.5346322.
• Li K, Zheng J, Li M, Zhou C, Lv H. (2009) A Novel Algorithm for Non-dominated Hypervolume-based Multiobjective Optimization, 2009 IEEE International Conference on Systems, Mans and Cybernetics -- SMC'09, San Antonio, 11th - 14th Oct 2009, DOI:10.1109/ICSMC.2009.5345983.

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