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Jun He 0004
Person information
- affiliation: Nottingham Trent University, School of Science and Technology, UK
- affiliation: Aberystwyth University, UK
- affiliation (former): University of Birmingham, UK
Other persons with the same name
- Jun He — disambiguation page
- Jun He 0001
— Uppsala University, Sweden (and 1 more)
- Jun He 0002 — National University of Singapore
- Jun He 0003 — University of Pittsburgh, PA, USA
- Jun He 0005 — Huawei Techologies, Nanjing, China
- Jun He 0006
- Jun He 0007
- Jun He 0008
- Jun He 0009
- Jun He 0010 — University of Arizona, USA (and 1 more)
- Jun He 0011 — University of Michigan-Dearborn, USA
- Jun He 0012 — Southwest University, School of Computer and Information Science, Chongqing, China
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2020 – today
- 2025
- [j47]Tao Xu
An adaptive helper and equivalent objective evolution strategy for constrained optimization. Inf. Sci. 690: 121536 (2025) - 2024
- [c53]Tao Xu
Accelerate Evolution Strategy by Proximal Policy Optimization. GECCO 2024 - [c52]Teena Rai
Understanding Feature Importance of Prediction Models Based on Lung Cancer Primary Care Data. IJCNN 2024: 1-8 - 2023
- [c51]Teena Rai
Decision Tree Approaches to Select High Risk Patients for Lung Cancer Screening Based on the UK Primary Care Data. AIME 2023: 35-39 - [c50]Azizkhon Afzalov, Ahmad Lotfi, Jun He
Coupled Assignment Strategy of Agents in Many Targets Environment. ICAART (1) 2023: 372-379 - [i30]Jun He, Yuren Zhou:
Drift Analysis with Fitness Levels for Elitist Evolutionary Algorithms. CoRR abs/2309.00851 (2023) - [i29]Jun He, Siang Yew Chong, Xin Yao:
Fast Estimations of Hitting Time of Elitist Evolutionary Algorithms from Fitness Levels. CoRR abs/2311.10502 (2023) - 2022
- [j46]Tao Xu
Helper and Equivalent Objectives: Efficient Approach for Constrained Optimization. IEEE Trans. Cybern. 52(1): 240-251 (2022) - [c49]Asmau Wali, Oluwasegun Apejoye, Thejavathy Raja, Jun He
A Novel Approach to Identifying DDoS Traffic in the Smart Home Network via Exploratory Data Analysis. AII 2022: 478-498 - 2021
- [j45]Yu Chen
Average convergence rate of evolutionary algorithms in continuous optimization. Inf. Sci. 562: 200-219 (2021) - [j44]Cong Wang
Error analysis of elitist randomized search heuristics. Swarm Evol. Comput. 63: 100875 (2021) - [c48]Abeer Alzubaidi
Selecting Lung Cancer Patients from UK Primary Care Data: A Longitudinal Study of Feature Trends. AII 2021: 43-59 - [c47]Asmau Wali, Oluwasegun Apejoye, Jun He, Xiaoqi Ma
An Exploratory Data Analysis of the Network Behavior of Hive Home Devices. IOTSMS 2021: 1-8 - [c46]Azizkhon Afzalov
Multi-Agent Path Planning Approach Using Assignment Strategy Variations in Pursuit of Moving Targets. KES-AMSTA 2021: 451-463 - [i28]Cong Wang, Yu Chen, Jun He, Xiufen Zou:
Influence of the Binomial Crossover on Performance of Randomized Search Heuristics. CoRR abs/2109.14195 (2021) - 2020
- [c45]Abdallah Naser
Heat-Map Based Occupancy Estimation Using Adaptive Boosting. FUZZ-IEEE 2020: 1-7 - [c44]Abdallah Naser
Human activity of daily living recognition in presence of an animal pet using thermal sensor array. PETRA 2020: 53:1-53:6 - [i27]Yu Chen, Jun He:
Exploitation and Exploration Analysis of Elitist Evolutionary Algorithms: A Case Study. CoRR abs/2001.10932 (2020)
2010 – 2019
- 2019
- [j43]Siang Yew Chong, Peter Tiño
Coevolutionary systems and PageRank. Artif. Intell. 277 (2019) - [j42]Rui Ding, Hongbin Dong
A novel two-archive strategy for evolutionary many-objective optimization algorithm based on reference points. Appl. Soft Comput. 78: 447-464 (2019) - [j41]Siang Yew Chong
A New Framework for Analysis of Coevolutionary Systems - Directed Graph Representation and Random Walks. Evol. Comput. 27(2): 195-228 (2019) - [j40]Jun Zhang, Jun He, Jiachuan Long
A New Denoising Method for UHF PD Signals Using Adaptive VMD and SSA-Based Shrinkage Method. Sensors 19(7): 1594 (2019) - [j39]Jinwei Pang, Jun He
Hybrid evolutionary programming using adaptive Lévy mutation and modified Nelder-Mead method. Soft Comput. 23(17): 7913-7939 (2019) - [j38]Wei Huang, Tao Xu
Multiobjective differential evolution enhanced with principle component analysis for constrained optimization. Swarm Evol. Comput. 50 (2019) - [j37]Yuren Zhou
A Scalar Projection and Angle-Based Evolutionary Algorithm for Many-Objective Optimization Problems. IEEE Trans. Cybern. 49(6): 2073-2084 (2019) - [c43]Cong Wang, Yu Chen
Estimating Approximation Errors of Elitist Evolutionary Algorithms. BIC-TA (1) 2019: 325-340 - [c42]Tao Xu
Helper and equivalent objective different evolution for constrained optimisation. GECCO (Companion) 2019: 9-10 - [c41]Jun He, Thomas Jansen
Unlimited budget analysis. GECCO (Companion) 2019: 427-428 - [c40]Yu Chen
Average Convergence Rate of Evolutionary Algorithms II: Continuous Optimisation. ISICA 2019: 31-45 - [c39]Tao Xu
A Multi-population Helper and Equivalent Objective Differential Evolution Algorithm. SSCI 2019: 2237-2244 - [i26]Cong Wang, Yu Chen, Jun He, Chengwang Xie:
Estimating Approximation Errors of Elitist Evolutionary Algorithms. CoRR abs/1909.00894 (2019) - [i25]Jun He, Thomas Jansen, Christine Zarges:
Unlimited Budget Analysis of Randomised Search Heuristics. CoRR abs/1909.03342 (2019) - 2018
- [j36]Xiaohui Li, Hongbin Dong, Yang Zhou, Jun He:
A Matching Approach to Factor Scores Based on Online Sponsored Search Auction. Int. J. Softw. Innov. 6(1): 11-30 (2018) - [j35]Kangshun Li, Yan Chen, Wei Li, Jun He
Improved gene expression programming to solve the inverse problem for ordinary differential equations. Swarm Evol. Comput. 38: 231-239 (2018) - [c38]Rui Ding, Hongbin Dong, Jun He, Xianbin Feng, Xiaodong Yu, Lijie Li:
U-NSGA-III: An Improved Evolutionary Many-Objective Optimization Algorithm. BIC-TA (1) 2018: 24-35 - [i24]Jun He, Tao Xu:
New Methods of Studying Valley Fitness Landscapes. CoRR abs/1805.00092 (2018) - [i23]Wei Huang, Tao Xu, Jun He, Kangshun Li:
Multiobjective Optimization Differential Evolution Enhanced with Principle Component Analysis for Constrained Optimization. CoRR abs/1805.00272 (2018) - [i22]Jun He, Yu Chen, Yuren Zhou:
A Theoretical Framework of Approximation Error Analysis of Evolutionary Algorithms. CoRR abs/1810.11532 (2018) - [i21]Yu Chen, Jun He:
Average Convergence Rate of Evolutionary Algorithms II: Continuous Optimization. CoRR abs/1810.11672 (2018) - 2017
- [j34]Dogan Corus
On Easiest Functions for Mutation Operators in Bio-Inspired Optimisation. Algorithmica 78(2): 714-740 (2017) - [j33]Jun He
Average Drift Analysis and Population Scalability. IEEE Trans. Evol. Comput. 21(3): 426-439 (2017) - [c37]Xiaohui Li, Yang Zhou, Hongbin Dong, Jun He:
Online sponsored search auction matching problem with advertiser credibility. ICIS 2017: 509-515 - [c36]Jun He, Yuren Zhou, Guangming Li:
An initial error analysis for evolutionary algorithms. GECCO (Companion) 2017: 317-318 - [c35]Wenjie Liu, Hongbin Dong, Jun He, Hongbo Shi:
A cooperative quantum particle swarm optimization based on multiple groups. SMC 2017: 3213-3218 - 2016
- [j32]Jun He
Average Convergence Rate of Evolutionary Algorithms. IEEE Trans. Evol. Comput. 20(2): 316-321 (2016) - [c34]Weichao Chai, Hongbin Dong, Jun He
A biogeography-based optimization algorithm with multiple migrations. ICIS 2016: 1-8 - [c33]Kangshun Li, Yan Chen, Jun He:
The Research of Solving Inverse Problems of Complex Differential Equations. BIC-TA (2) 2016: 518-523 - [c32]Rui Ding, Hongbin Dong, Jun He
An improved partheno-genetic algorithm for the multi-constrained problem of curling match arrangement. CEC 2016: 957-964 - [c31]Jinwei Pang, Hongbin Dong, Jun He
Mixed mutation strategy evolutionary programming based on Shapley value. CEC 2016: 2805-2812 - [c30]Jun He
An analytic expression of relative approximation error for a class of evolutionary algorithms. CEC 2016: 4366-4373 - [c29]Tao Xu
A New Multi-objective Model for Constrained Optimisation. UKCI 2016: 71-85 - 2015
- [j31]Tobias Friedrich, Jun He, Thomas Jansen, Alberto Moraglio
Genetic and Evolutionary Computation. Theor. Comput. Sci. 561: 1-2 (2015) - [j30]Jun He
On the Easiest and Hardest Fitness Functions. IEEE Trans. Evol. Comput. 19(2): 295-305 (2015) - [c28]Hongbin Dong, Xuyang Teng, Yang Zhou, Jun He
Feature subset selection using dynamic mixed strategy. CEC 2015: 672-679 - [c27]Jun He
Analysis of Solution Quality of a Multiobjective Optimization-Based Evolutionary Algorithm for Knapsack Problem. EvoCOP 2015: 74-85 - [c26]Dogan Corus
On Easiest Functions for Somatic Contiguous Hypermutations And Standard Bit Mutations. GECCO 2015: 1399-1406 - [e1]Jun He, Thomas Jansen, Gabriela Ochoa, Christine Zarges:
Proceedings of the 2015 ACM Conference on Foundations of Genetic Algorithms XIII, Aberystwyth, United Kingdom, January 17 - 20, 2015. ACM 2015, ISBN 978-1-4503-3434-1 [contents] - [i20]Jun He, Yong Wang, Yuren Zhou:
Analysis of Solution Quality of a Multiobjective Optimization-based Evolutionary Algorithm for Knapsack Problem. CoRR abs/1502.03699 (2015) - [i19]Jun He, Guangming Lin:
Average Convergence Rate of Evolutionary Algorithms. CoRR abs/1504.08117 (2015) - [i18]Jun He, Tao Xu:
Multi-objective Differential Evolution with Helper Functions for Constrained Optimization. CoRR abs/1509.09060 (2015) - 2014
- [j29]Xinsheng Lai, Yuren Zhou, Jun He
Performance Analysis of Evolutionary Algorithms for the Minimum Label Spanning Tree Problem. IEEE Trans. Evol. Comput. 18(6): 860-872 (2014) - [c25]Jun He
A theoretical assessment of solution quality in evolutionary algorithms for the knapsack problem. IEEE Congress on Evolutionary Computation 2014: 141-148 - [i17]Jun He, Feidun He, Hongbin Dong:
A Novel Genetic Algorithm using Helper Objectives for the 0-1 Knapsack Problem. CoRR abs/1404.0868 (2014) - [i16]Jun He, Boris Mitavskiy, Yuren Zhou:
A Theoretical Assessment of Solution Quality in Evolutionary Algorithms for the Knapsack Problem. CoRR abs/1404.3520 (2014) - [i15]Xinsheng Lai, Yuren Zhou, Jun He, Jun Zhang:
Performance Analysis on Evolutionary Algorithms for the Minimum Label Spanning Tree Problem. CoRR abs/1409.1073 (2014) - 2013
- [j28]Boris Mitavskiy, Elio Tuci, Chris Cannings, Jonathan E. Rowe, Jun He
Geiringer theorems: from population genetics to computational intelligence, memory evolutive systems and Hebbian learning. Nat. Comput. 12(4): 473-484 (2013) - [c24]Jun He
Mixed strategy may outperform pure strategy: An initial study. IEEE Congress on Evolutionary Computation 2013: 562-569 - [c23]Boris Mitavskiy, Jun He
Combining drift analysis and generalized schema theory to design efficient hybrid and/or mixed strategy EAs. IEEE Congress on Evolutionary Computation 2013: 2028-2036 - [c22]Boris Mitavskiy, Jun He
A further generalization of the finite-population geiringer-like theorem for pomdps to allow recombination overarbitrary set covers. FOGA 2013: 133-146 - [i14]Jun He, Wei Hou, Hongbin Dong, Feidun He:
Mixed Strategy May Outperform Pure Strategy. CoRR abs/1303.3154 (2013) - [i13]Boris Mitavskiy, Jun He:
Combining Drift Analysis and Generalized Schema Theory to Design Efficient Hybrid and/or Mixed Strategy EAs. CoRR abs/1305.2490 (2013) - [i12]Boris Mitavskiy, Jun He:
A Further Generalization of the Finite-Population Geiringer-like Theorem for POMDPs to Allow Recombination Over Arbitrary Set Covers. CoRR abs/1305.2498 (2013) - [i11]Boris Mitavskiy, Elio Tuci, Chris Cannings, Jonathan E. Rowe, Jun He:
Geiringer Theorems: From Population Genetics to Computational Intelligence, Memory Evolutive Systems and Hebbian Learning. CoRR abs/1305.2504 (2013) - [i10]Jun He, Xin Yao:
Average Drift Analysis and Population Scalability. CoRR abs/1308.3080 (2013) - [i9]Boris Mitavskiy, Jun He:
Design and Analysis of an Estimation of Distribution Approximation Algorithm for Single Machine Scheduling in Uncertain Environments. CoRR abs/1312.1273 (2013) - [i8]Jun He, Feidun He, Xin Yao:
A Unified Markov Chain Approach to Analysing Randomised Search Heuristics. CoRR abs/1312.2368 (2013) - 2012
- [c21]Boris Mitavskiy, Jun He
A polynomial time approximation scheme for a single machine scheduling problem using a hybrid evolutionary algorithm. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c20]Jun He
Pure Strategy or Mixed Strategy? - An Initial Comparison of Their Asymptotic Convergence Rate and Asymptotic Hitting Time. EvoCOP 2012: 218-229 - [c19]Xin Zhang, Hongbin Dong, Xue Yang, Jun He
A Mixed Strategy Multi-Objective Coevolutionary Algorithm Based on Single-Point Mutation and Particle Swarm Optimization. RSKT 2012: 174-184 - [i7]Boris Mitavskiy, Jun He:
A Polynomial Time Approximation Scheme for a Single Machine Scheduling Problem Using a Hybrid Evolutionary Algorithm. CoRR abs/1202.1708 (2012) - [i6]Jun He, Tianshi Chen:
A General Analysis of Evolutionary Algorithms for Hard and Easy Fitness Functions. CoRR abs/1203.6286 (2012) - [i5]Simon T. Powers, Jun He:
A hybrid artificial immune system and Self Organising Map for network intrusion detection. CoRR abs/1208.0541 (2012) - 2011
- [j27]Yu Chen
Drift conditions for estimating the first hitting times of evolutionary algorithms. Int. J. Comput. Math. 88(1): 37-50 (2011) - [i4]Jun He, Tianshi Chen:
Population Scalability Analysis of Abstract Population-based Random Search: Spectral Radius. CoRR abs/1108.4531 (2011) - [i3]Jun He, Feidun He, Hongbin Dong:
Pure Strategy or Mixed Strategy? CoRR abs/1112.1517 (2011) - 2010
- [j26]Tobias Friedrich, Jun He
Approximating Covering Problems by Randomized Search Heuristics Using Multi-Objective Models. Evol. Comput. 18(4): 617-633 (2010) - [j25]Tianshi Chen, Jun He
Choosing selection pressure for wide-gap problems. Theor. Comput. Sci. 411(6): 926-934 (2010) - [c18]Jun He
A note on the first hitting time of (1 + lambda) evolutionary algorithm for linear functions with boolean inputs. IEEE Congress on Evolutionary Computation 2010: 1-6 - [c17]Liang Shen, Jun He
A mixed strategy for Evolutionary Programming based on local fitness landscape. IEEE Congress on Evolutionary Computation 2010: 1-8
2000 – 2009
- 2009
- [j24]Yuren Zhou, Jun He
A comparative runtime analysis of heuristic algorithms for satisfiability problems. Artif. Intell. 173(2): 240-257 (2009) - [j23]Tobias Friedrich, Jun He
Analyses of Simple Hybrid Algorithms for the Vertex Cover Problem. Evol. Comput. 17(1): 3-19 (2009) - [j22]Jun He
A mixed strategy of combining evolutionary algorithms with multigrid methods. Int. J. Comput. Math. 86(5): 837-849 (2009) - [j21]Pietro S. Oliveto
Analysis of the (1+1) -EA for Finding Approximate Solutions to Vertex Cover Problems. IEEE Trans. Evol. Comput. 13(5): 1006-1029 (2009) - [j20]Tianshi Chen, Jun He
A New Approach for Analyzing Average Time Complexity of Population-Based Evolutionary Algorithms on Unimodal Problems. IEEE Trans. Syst. Man Cybern. Part B 39(5): 1092-1106 (2009) - 2008
- [j19]Simon T. Powers, Jun He
A hybrid artificial immune system and Self Organising Map for network intrusion detection. Inf. Sci. 178(15): 3024-3042 (2008) - [c16]Pietro S. Oliveto
Analysis of population-based evolutionary algorithms for the vertex cover problem. IEEE Congress on Evolutionary Computation 2008: 1563-1570 - [i2]Jun He, Yuren Zhou, Xin Yao:
A Comparison of GAs Penalizing Infeasible Solutions and Repairing Infeasible Solutions on the 0-1 Knapsack Problem. Theory of Evolutionary Algorithms 2008 - 2007
- [j18]Jun He
A Note on Problem Difficulty Measures in Black-Box Optimization: Classification, Realizations and Predictability. Evol. Comput. 15(4): 435-443 (2007) - [j17]Pietro S. Oliveto
Time complexity of evolutionary algorithms for combinatorial optimization: A decade of results. Int. J. Autom. Comput. 4(3): 281-293 (2007) - [j16]Yuren Zhou, Jun He
Convergence analysis of a self-adaptive multi-objective evolutionary algorithm based on grids. Inf. Process. Lett. 104(4): 117-122 (2007) - [j15]Hongbin Dong, Jun He
Evolutionary programming using a mixed mutation strategy. Inf. Sci. 177(1): 312-327 (2007) - [j14]Yuren Zhou, Jun He
A Runtime Analysis of Evolutionary Algorithms for Constrained Optimization Problems. IEEE Trans. Evol. Comput. 11(5): 608-619 (2007) - [c15]Pietro S. Oliveto
Evolutionary algorithms and the Vertex Cover problem. IEEE Congress on Evolutionary Computation 2007: 1870-1877 - [c14]Tobias Friedrich, Jun He
On improving approximate solutions by evolutionary algorithms. IEEE Congress on Evolutionary Computation 2007: 2614-2621 - [c13]Tobias Friedrich, Nils Hebbinghaus, Frank Neumann
Approximating covering problems by randomized search heuristics using multi-objective models. GECCO 2007: 797-804 - [c12]Jun He
A comparison of GAs using penalizing infeasible solutions and repairing infeasible solutions on restrictive capacity knapsack problem. GECCO 2007: 1518 - [c11]Jun He
A Comparison of GAs Using Penalizing Infeasible Solutions and Repairing Infeasible Solutions on Average Capacity Knapsack. ISICA 2007: 100-109 - [c10]Yuren Zhou, Zhi Guo, Jun He:
On the Running Time Analysis of the (1+1) Evolutionary Algorithm for the Subset Sum Problem. LSMS (1) 2007: 73-82 - [i1]Tobias Friedrich, Jun He, Nils Hebbinghaus, Frank Neumann, Carsten Witt:
Approximating Covering Problems by Randomized Search Heuristics Using Multi-Objective Models. Electron. Colloquium Comput. Complex. TR07 (2007) - 2006
- [j13]Xin Yao
Current developments and future directions of bio-inspired computation and implications for ecoinformatics. Ecol. Informatics 1(1): 9-22 (2006) - [c9]Jun He, Xin Yao:
Analysis of Scalable Parallel Evolutionary Algorithms. IEEE Congress on Evolutionary Computation 2006: 120-127 - 2005
- [j12]Jun He
A comparative study of three evolutionary algorithms incorporating different amounts of domain knowledge for node covering problem. IEEE Trans. Syst. Man Cybern. Part C 35(2): 266-271 (2005) - [c8]Jun He
A Game-Theoretic Approach for Designing Mixed Mutation Strategies. ICNC (3) 2005: 279-288 - [c7]Yuren Zhou, Jun He:
The Convergence of a Multi-objective Evolutionary Algorithm Based on Grids. ICNC (2) 2005: 1015-1024 - [c6]Hongbin Dong, Jun He
A Mixed Mutation Strategy Evolutionary Programming Combined with Species Conservation Technique. MICAI 2005: 593-602 - 2004
- [j11]Jun He
Time Complexity Analysis of an Evolutionary Algorithm for Finding Nearly Maximum Cardinality Matching. J. Comput. Sci. Technol. 19(4): 450-458 (2004) - [j10]Jun He
A study of drift analysis for estimating computation time of evolutionary algorithms. Nat. Comput. 3(1): 21-35 (2004) - [c5]Jun He, Xin Yao, Qingfu Zhang:
To understand one-dimensional continuous fitness landscapes by drift analysis. IEEE Congress on Evolutionary Computation 2004: 1248-1253 - [c4]Xiufen Zou, Minzhong Liu, Lishan Kang, Jun He:
A High Performance Multi-objective Evolutionary Algorithm Based on the Principles of Thermodynamics. PPSN 2004: 922-931 - 2003
- [j9]Jun He
Towards an analytic framework for analysing the computation time of evolutionary algorithms. Artif. Intell. 145(1-2): 59-97 (2003) - [c3]Yuren Zhou, Yuanxing Li, Jun He, Lishan Kang:
Multi-objective and MGG evolutionary algorithm for constrained optimization. IEEE Congress on Evolutionary Computation 2003: 1-5 - [c2]Jun He, Xin Yao
An analysis of evolutionary algorithms for finding approximation solutions to hard optimisation problems. IEEE Congress on Evolutionary Computation 2003: 2004-2010 - 2002
- [j8]Jun He
Erratum to: Drift analysis and average time complexity of evolutionary algorithms [Artificial Intelligence 127 (2001) 57-85]. Artif. Intell. 140(1/2): 245-248 (2002) - [j7]Jun He
From an individual to a population: an analysis of the first hitting time of population-based evolutionary algorithms. IEEE Trans. Evol. Comput. 6(5): 495-511 (2002) - 2001
- [j6]Jun He
Drift analysis and average time complexity of evolutionary algorithms. Artif. Intell. 127(1): 57-85 (2001) - [j5]Lishan Kang, Yuanxiang Li, Zhengjun Pan, Jun He
Massively parallel algorithms from physics and biology. Int. J. Comput. Math. 77(2): 201-250 (2001) - [j4]Jun He
Conditions for the convergence of evolutionary algorithms. J. Syst. Archit. 47(7): 601-612 (2001) - 2000
- [j3]Jun He
Solving equations by hybrid evolutionary computation techniques. IEEE Trans. Evol. Comput. 4(3): 295-304 (2000)
1990 – 1999
- 1999
- [j2]Jun He
On the Convergence Rates of Genetic Algorithms. Theor. Comput. Sci. 229(1): 23-39 (1999) - 1995
- [j1]Jun He
Convergence of Genetic Evolution Algorithms for Optimization. Parallel Algorithms Appl. 5(1-2): 37-56 (1995) - 1994
- [c1]Zhengjun Pan, Lishan Kang, Jun He
An Evolutionary Approach to Adaptive Model-Building. Evo Workshops 1994: 236-244
Coauthor Index
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