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2011
|
1.
|
 Y. Chen, X.
Zou and J. He.
Drift Conditions for
Estimating the First Hitting Times of Evolutionary Algorithm.
International
Journal
of
Computer
Mathematics. 88(1): 37-50, 2011. |
|
2010
|
2.
|
T.
Friedrich, J. He , N.
Hebbinghaus, F.
Neumann and C. Witt. Approximating
Covering
Problems
by
Randomized
Search
Heuristics
using
Multi-Objective
Models. Evolutionary
Computation.
18(4): 617-633, 2010. |
3.
|
T. Chen, J.
He, G. Chen and X. Yao. Choosing
selection
pressure
for
wide-gap
problems. Theoretical
Computer
Science. 411(6):926-934,2010.
|
4
|
 J. He. A
Note on the First
Hitting Time of (1+N) Evolutionary Algorithm
for Linear Functions
with Boolean Inputs. In Proceedings
of
2010
IEEE
Congress
on
Evolutionary
Computation,
pp.527-532. IEEE Press, 2010. |
5.
|
L. Shen and J. He. A
Mixed Strategy
for Evolutionary Programming Based on Local Fitness
Landscape. In Proceedings
of
2010
IEEE
Congress
on
Evolutionary
Computation, pp. 350-357. IEEE Press, 2010. |
6.
|
 J. He. Complexity in
Adaptive Systems. In Encyclopedia
of
Machine
Learning, Springer, 2010. |
|
2009 |
7.
|
P. S.
Oliveto, J. He , and
X. Yao. Analysis
of
the
(1+1)-EA
for
Finding
Approximate
Solutions
to Vertex Cover Problems.
IEEE Transactions on Evolutionary Computation, 13
(5):1006 -1029, 2009.
|
8.
|
T.
Chen, J. He,
G.
Sun,
G.
Chen,
and
X.
Yao,
A
New Approach for Analyzing Average Time Complexity of Population-based
Evolutionary Algorithms on Unimodal Problems.
IEEE Transactions on Systems, Man and Cybernetics, Part B, 39
(5):1092-1106, 2009.
|
9.
|
J. He, and L. Kang. A Mixed Strategy of Combining Evolutionary Algorithms
with Multigrid Methods. International
Journal
of
Computer
Mathematics, 86(5):837-849,
2009. |
10.
|
Y. Zhou, J. He, and Q. Nie. A Comparative Runtime Analysis of Heuristic Algorithms
for Satisfiability Problems. Artificial Intelligence, 173(2):240-257,
2009.
|
11.
|
T.
Friedrich, J. He, N.
Hebbinghaus, F.
Neumann and C. Witt. Analyses
of
Simple
Hybrid
Algorithms
for
the
Vertex
Cover
Problem.
Evolutionary Computation, 17
(1):3-19, 2009. |
|
2008
|
12.
|
S. Powers
and J. He. A
Hybrid Artificial Immune System and Self Organising Map for Network
Intrusion Detection. Information
Sciences, 178 (15): 3024-3042, 2008. |
13.
|
A. Bennett,
R. Johnston, E. Turpin
and J. He,
Analysis of an Immune Algorithm for Protein Structure
Prediction. Informatica, 32
(3): 245-251, 2008.
|
14.
|
P.S.
Oliveto, J.He and X.Yao. Analysis
of
Population-based
Evolutionary
Algorithms
for the Vertex Cover Problem. In
Proceedings of IEEE CEC 2008, pp.1563-1570. IEEE Press
2008.
|
|
2007
|
15.
|
J. He,
C. Reeves, C. Witt and X. Yao. A
Note on Problem Difficulty Measures in Black-Box
Optimization: Classification, Existence and Predictability. Evolutionary Computation, 15
(4):435-443, 2007 |
16.
|
Y. Zhou and
J. He. A
runtime
analysis of evolutionary algorithms for constrained optimization
problems. IEEE
Transactions
on
Evolutionary
Computation, 11(5):608-619, 2007.
|
17.
|
P. S.
Oliveto, J. He, and
X. Yao. Time
Complexity
of
Evolutionary
Algorithms for
Combinatorial Optimization: A Decade of Results. International
Journal
of
Automation
and
Computing,
4
(3):281-293, 2007. |
18.
|
H. Dong, J. He, H. Huang and W. Hou.
Evolutionary
programming
using
a
mixed
mutation
strategy. Information Sciences. 177 (1):
312-327, 2007.
|
19.
|
H. Dong, J. He, H. Huang and W. Hou.
Evolutionary
programming
using
a
mixed
mutation
strategy. Information Sciences. 177 (1):
312-327, 2007.
|
20.
|
J. He
and Y.Zhou. A
Comparison
of
GAs
using
Penalizing
Infeasible
Solutions
and
Repairing
Infeasible
Solutions
on
Average
Capacity
Knapsack.
In
Proceedings of ISICA'2007(LNCS 4683), pp.102-110. Springer
Verlag. 2007. |
21.
|
T.
Friedrich, J. He, N.
Hebbinghaus, F.
Neumann, C. Witt. Approximating
Covering
Problems
by
Randomized
Search
Heuristics
Using
Multi-Objective
Models. In
Proceedings of GECCO'2007, pp.797-804. 2007.
|
|
2006
|
22.
|
X. Yao, Y.
Liu, J. Li, J. He,
and C. Frayn.
Current developments and future directions of
bio-inspired computation and implications for ecoinformatics.
Ecological Informatics. 1 (1): 9--22,
2006.
|
23.
|
J. He
and X.
Yao.
Analysis of
Scalable Parallel Evolutionary Algorithms. In
Proceedings
of IEEE CEC'2006, pp.120- 127 . IEEE Press. 2006.
|
|
2005
|
24.
|
J. He,
X.
Yao and J. Li. A
Comparative
Study of Three Evolutionary Algorithms Incorporating Different Amount
of Domain Knowledge for Node Covering Problems,
IEEE Transactions on Systems, Man and Cybernetics, Part C. 35(2):266-
271,
2005.
|
25.
|
J. He and
X. Yao. A game-theoretic approach for designing mixed
mutation strategies. In Proceedings of ICNC'05 (
LNCS 3612) , pp.279-288. Springer Verlag. 2005.
|
26.
|
Y. Zhou and J. He. The
Convergence of a Multi-objective Evolutionary Algorithm Based on Grids.
In Proceedings of ICNC'05 (LNCS 3611), pp.1015-1024.
Springer Verlag. 2005. |
27.
|
H. Dong, J. He , H. Huang and W.
Hou. A Mixed Mutation Strategy Evolutionary Programming
Combined with Species Conservation Technique. In Proceedings
of MICAI 2005 (LNCS 3789), pp.593-602. Springer Verlag. 2005.
|
|
2004
|
28.
|
J. He
and X. Yao. A Study of Drift Analysis for Estimating Computation
Time of Evolutionary Algorithms. Natural Computing,
3 (1):21-35, 2004. |
29.
|
J. He and
X. Yao. Time
complexity analysis of an evolutionary algorithm for finding nearly
maximum cardinality matching. Journal of Computer
Science
and Technology, 19 (4):450--458, 2004. |
30.
|
X. Zou, M.
Liu, L. Kang and J. He.
A High
Performance Multi-objective Evolutionary Algorithm Based on the
Principles of Thermodynamics. In Proceedings
of PPSN VIII (LNCS 3242), pp.922-931. Springer Verlag. 2004.
|
31.
|
J. He,
X.
Yao,
and
Q.F.
Zhang. To
understand
one-dimensional continuous fitness landscapes by drift analysis. In
Proceedings of IEEE CEC'2004, pp.1248 - 1253. IEEE Press.
2004. |
|
2003
|
32.
|
J. He and
X. Yao.
Towards an Analytic
Framework for Analysing the Computation Time of Evolutionary
Algorithms.
Artificial Intelligence, 145 (1-2):59-97, 2003. |
33.
|
J. He
and X. Yao. Drift
analysis in studying the convergence and hitting times of evolutionary
algorithms: An overview. Wuhan
University
Journal
of
Natural
Sciences, 8
1:143-154, 2003. |
34.
|
J. He and
X. Yao. An
analysis of
evolutionary algorithms for finding approximation solutions to hard
optimisation problems. In
Proceedings
of IEEE CEC'2003, pp.2004-2010. IEEE Press. 2003. |
|
2002
|
35.
|
J. He and
X. Yao.
From an Individual
to a Population: An Analysis of the First Hitting Time of
Population-based Evolutionary Algorithms. IEEE
Transactions
on
Evolutionary
Computation, 6(5):495-511, 2002.
|
|
2001
|
36.
|
J. He
and X. Yu. Conditions for the convergence of evolutionary
algorithms. Journal
of Systems Architecture, 47 (7):601-612, 2001.
|
37.
|
L.
Kang, Y. X. Li, Z.
Pan, J. He, and
D. J. Evans. Massively
parallel
algorithms
from
physics
and
biology.
International
Journal
of
Computer
Mathematics, 77 (2):201--250, 2001. |
38.
|
J. He
and
X. Yao. Drift Analysis and
Average Time Complexity of Evolutionary Algorithms
Artificial Intelligence, 127 (1):57-85, 2001. (Erratum
in
Artificial Intelligence, 140 (1):245-248, 2002). |
|
2000
|
39.
|
J. He,
J. Y. Xu, and X. Yao. Solving
equations
by hybrid evolutionary computation techniques.
IEEE Transactions on Evolutionary Computation, 4
(3):295-304, 2000.
|
|
1999
|
40.
|
J. He and
L. S. Kang. On the
convergence rate of genetic algorithms.
Theoretical Computer Science, 229 (1-2):23-39, 1999. |
|
1997
|
41.
|
D. H. Ji, J. He , and C. Huang.
Learning new compositions from given ones. In
Proceedings of CoNLL-97 , pp.25-32. Association for
Computational Linguistics. 1997.
|
|
1996
|
42.
|
J. He, L. Kang and
Y. Chen. Multiple
structure computational model and its application in
optimization. Wuhan
University
Journal
of
Natural
Sciences, 1
(3-4):593-598, 1996. |
|
1995
|
43.
|
J. He, L. Kang and Y. Chen Convergence of Genetic Evolution Algorithms for
Optimization.
Parallel Algorithms and Applications, 5 (1):37-56,
1995. |
