Research
My research is in evolutionary computation. My current work focuses on constraint handling and on the use of surrogate modelling techniques. I also have research interests in neighbouring areas of optimization and machine learning.
A complete listing of publications can be found below or on my
Google
scholar page.
Teaching
In 2023/24 I teach the following courses:
CSCI 6514: Strategies for Search and Optimization
(Fall term)
CSCI 1300: Calculus in Computer Science
(Winter term)
CSCI 3162: Digital Media
(Winter term)
Course matrials and further information are available on Brightspace.
Publications
Book
D. V. Arnold
Noisy Optimization with Evolution
Strategies
Kluwer Academic Publishers, 2002.
Journal Papers
P. Spettel, Z. Ba, and D. V. Arnold
Active sets for
explicitly constrained evolutionary optimization
Evolutionary Computation, 30(4):531553, 2022.
X. Gao, S. Brooks, and D. V. Arnold
A featurebased quality
metric for tone mapped images
ACM Transactions on Applied Perception, 14(4), 26:126:11, 2017.
M. Hellwig and D. V. Arnold
Comparison of
constraint handling mechanisms for the (1,λ)ES on a simple
constrained problem
Evolutionary Computation, 24(1):123, 2016.
X. Gao, S. Brooks, and D. V. Arnold
Automated parameter
tuning for tone mapping using visual saliency
Computers & Graphics, 52:171180, 2015.
D. V. Arnold
On the behaviour of the
(1,λ)ES for conically constrained linear problems
Evolutionary Computation, 22(3):503523, 2014.
D. V. Arnold
Resampling versus repair
in evolution strategies applied to a constrained linear
problem
Evolutionary Computation, 21(3):389411, 2013.
G. LeBlanc, A. Shouldice, D. V. Arnold, and S. Brooks
Multiband
Fourier synthesis of ocean waves
Journal of Graphics Tools, 16(2):5770, 2012.
D. V. Arnold and H.G. Beyer
On the behaviour of
evolution strategies optimising cigar functions
Evolutionary Computation, 18(4):661682, 2010.
T. Burrell, D. Arnold, and S. Brooks
Advected river
textures
Computer Animation and Virtual Worlds, 20(23):163173, 2009.
D. V. Arnold and H.G. Beyer
Evolution
strategies with cumulative step length adaptation on the noisy parabolic
ridge
Natural Computing, 7(4):555587, 2008.
D. V. Arnold and A. MacLeod
Step length
adaptation on ridge functions
Evolutionary Computation, 16(2):151184, 2008.
D. V. Arnold and R. Salomon
Evolutionary
gradient search revisited
IEEE Transactions on Evolutionary Computation, 11(4):480495, 2007.
D. V. Arnold and H.G. Beyer
Optimum tracking with evolution strategies
Evolutionary Computation, 14(3):291308, 2006.
D. V. Arnold
Weighted
multirecombination evolution strategies
Theoretical Computer Science, 361(1):1837, 2006.
D. V. Arnold and H.G. Beyer
A general noise
model and its effects on evolution strategy performance
IEEE Transactions on Evolutionary Computation, 10(4):380391, 2006.
D. V. Arnold and H.G. Beyer
Expected sample
moments of concomitants of selected order statistics
Statistics and Computing, 15(3):241250, 2005.
H.G. Beyer, D. V. Arnold, and S. MeyerNieberg
A new approach for
predicting the final outcome of evolution strategy optimization under
noise
Genetic Programming and Evolvable Machines, 6(1):724, 2005.
D. V. Arnold and H.G. Beyer
Performance analysis
of evolutionary optimization with cumulative step length
adaptation
IEEE Transactions on Automatic Control, 49(4):617622, 2004.
D. V. Arnold and H.G. Beyer
On the benefits of
populations for noisy optimization
Evolutionary Computation, 11(2):111127, 2003.
D. V. Arnold and H.G. Beyer
A comparison of
evolution strategies with other direct search methods in the presence of
noise
Computational Optimization and Applications, 24(1):135159, 2003.
H.G. Beyer and D. V. Arnold
Qualms regarding
the optimality of cumulative path length control in CSA/CMAevolution
strategies
Evolutionary Computation, 11(1):1928, 2003.
D. V. Arnold and H.G. Beyer
Performance
analysis of evolution strategies with multirecombination in
highdimensional R^{N}search spaces disturbed by
noise
Theoretical Computer Science, 289(1):629647, 2002.
D. V. Arnold and H.G. Beyer
Local performance of the
(1+1)ES in a noisy environment
IEEE Transactions on Evolutionary Computation, 6(1):3041, 2002.
R. F. Hadley, A. RotaruVarga, D. V. Arnold, and V. C. Cardei
Syntactic
systematicity arising from semantic predictions in a Hebbiancompetitive
network
Connection Science, 13(1):7394, 2001.
D. V. Arnold
Informationtheoretic analysis of phase transitions
Complex Systems, 10(2):143155, 1996.
Book Chapters
N. Hansen, D. V. Arnold, and A. Auger
Evolution
strategies
in J. Kacprzyk and W. Pedrycz (eds.),
Handbook of
Computational Intelligence,
Springer, 2015.
J. Porter and D. V. Arnold
Analyzing the
behaviour of multirecombinative evolution strategies applied to a
conically constrained problem
in R. Datta and K. Deb (eds.), Evolutionary Constrained Optimization,
Springer, 2015.
R. Salomon and D. V. Arnold
The
evolutionarygradientsearch procedure in theory and practice
in R. Chiong (ed.), NatureInspired Algorithms for Optimisation.
Springer, 2009.
D. V. Arnold
Evolution strategies in noisy environments — A survey of existing
work
in L. Kallel et al. (eds.), Theoretical Aspects of Evolutionary
Computing. Springer, 2001.
H.G. Beyer and D. V. Arnold
Theory of evolution strategies — A tutorial
in L. Kallel et al. (eds.), Theoretical Aspects of Evolutionary
Computing. Springer, 2001.
Refereed Conference and Workshop Papers
Y. Hong and D. V. Arnold
Evolutionary
mixedinteger optimization with explicit constraints
Genetic and Evolutionary Computation Conference. Lisbon, 2023.
A. Abbasnejad and D. V. Arnold
Adaptive function
value warping for surrogate model assisted evolutionary
optimization
Parallel Problem Solving from Nature — PPSN XVII. Dortmund, 2022.
L. Toal and D. V. Arnold
Simple
surrogate model assisted optimization with covarianve matrix
adaptation
Parallel Problem Solving from Nature — PPSN XVI. Leiden, 2020.
J. Yang and D. V. Arnold
corrected version
A surrogate model
assisted (1+1)ES with increased exploitation of the model
Genetic and Evolutionary Computation Conference. Prague, 2019.
A. Kayhani and D. V. Arnold
Design of a
surrogate model assisted (1+1)ES
Parallel Problem Solving from Nature — PPSN XV. Coimbra, 2018.
X. Gao, J. Porter, S. Brooks, and D. V. Arnold
Evolutionary
optimization of tone mapped image quality index
Evolution Artificielle. Paris, 2017.
D. V. Arnold
Reconsidering
constraint release for activeset evolution strategies
Genetic and Evolutionary Computation Conference. Berlin, 2017.
D. V. Arnold
An activeset
evolution strategy for optimization with known constraints
Parallel Problem Solving from Nature — PPSN XIV. Edinburgh, 2016.
A. Lu and D. V. Arnold
An evolutionary
algorithm for depth image based camera pose estimation in indoor
environments
IEEE Congress on Evolutionary Computation. Vancouver, 2016.
X. Gao, S. Brooks, and D. V. Arnold
Automatic blended
tone mapping through evolutionary optimization
IEEE Congress on Evolutionary Computation. Vancouver, 2016.
D. V. Arnold and J. Porter
Best Paper Award, Continuous Optimization
Track
Towards an augmented
Lagrangian constraint handling approach for the (1+1)ES
Genetic and Evolutionary Computation Conference. Madrid, 2015.
X. Gao, S. Brooks, and D. V. Arnold
Saliencybased
parameter tuning for tone mapping
11th European Conference on Visual Media Production. London, 2014.
D. V. Arnold
On the use of
evolution strategies for optimization on spherical manifolds
Parallel Problem Solving from Nature — PPSN XIII. Ljubljana, 2014.
S. Nourashrafeddin, E. Milios, and D. V. Arnold
Best Student Paper Award
An ensemble approach
for text document clustering using Wikipedia concepts
ACM Symposium on Document Engineering. Fort Collins, 2014.
K. Fraser, D. V. Arnold, and G. Dellaire
Projected
BarzilaiBorwein method with infeasible iterates for nonnegative
leastsquares image deblurring
Computer and Robot Vision. Montreal, 2014
S. Nourashrafeddin, E. Milios and D. V. Arnold
Interactive text
document clustering using feature labeling
ACM Symposium on Document Engineering. Florence, 2013.
X. Gao, S. Brooks, and D. V. Arnold
Virtual photograph
based saliency analysis of high dynamic range images
International Symposium on Computational Aesthetics in Graphics,
Visualization, and Imaging. Anaheim, 2013.
D. V. Arnold
Best Paper Award, ES/EP Track
On the behaviour of
the (1,λ)ES for a conically constrained problem
Genetic and Evolutionary Computation Conference. Amsterdam, 2013.
S. Nourashrafeddin, E. Milios and D. V. Arnold
An evolutionary
algorithm for feature selective double clustering of text
documents
IEEE Congress on Evolutionary Computation. Cancun, 2013.
J. Porter and D. V. Arnold
An evolutionary
spline fitting algorithm for identifying filamentous
cyanobacteria
ACM Symposium on Applied Computing. Coimbra, 2013.
D. V. Arnold
Best Paper Award
On the behaviour
of the (1,λ)σSAES for a constrained linear
problem
Parallel Problem Solving from Nature — PPSN XII. Taormina, 2012.
D. V. Arnold and N. Hansen
A (1+1)CMAES for
constrained optimisation
Genetic and Evolutionary Computation Conference. Philadelphia, 2012.
D. V. Arnold
Analysis of a repair
mechanism for the (1,λ)ES applied to a simple constrained
problem
Genetic and Evolutionary Computation Conference. Dublin, 2011.
D. V. Arnold
On the behaviour of
the (1,λ)ES for a simple constrained problem
Foundations of Genetic Algorithms, 11. Schwarzenberg, Austria, 2011.
D. Brockhoff, A. Auger, N. Hansen, D. V. Arnold, and T. Hohm
Mirrored
sampling and sequential selection for evolution
strategies
Parallel Problem Solving from Nature — PPSN XI. Krakow, 2010.
D. V. Arnold and N. Hansen
Best Paper Award, ES/EP Track
Active covariance
matrix adaptation for the (1+1)CMAES
Genetic and Evolutionary Computation Conference. Portland, OR, 2010.
D. V. Arnold and A. S. Castellarin
A novel approach to
adaptive isolation in evolution strategies
Genetic and Evolutionary Computation Conference. Montreal, 2009.
S. B. Chisholm, D. V. Arnold, and S. Brooks
Tone mapping by
interactive evolution
Genetic and Evolutionary Computation Conference. Montreal, 2009.
D. V. Arnold, H.G. Beyer, and A. Melkozerov
On the behaviour
of weighted multirecombination evolution strategies optimising noisy
cigar functions
Genetic and Evolutionary Computation Conference. Montreal, 2009.
D. V. Arnold and D. Brauer
On the behaviour
of the (1+1)ES for a simple constrained problem
Parallel Problem Solving from Nature — PPSN X. Dortmund, 2008.
D. V. Arnold and D. C. S. Van Wart
Cumulative step
length adaptation for evolution strategies using negative recombination
weights
EvoWorkshops 2008. Napoli, 2008.
D. V. Arnold
On the use of
evolution strategies for optimising certain positive definite quadratic
forms
Genetic and Evolutionary Computation Conference. London, 2007.
D. V. Arnold
Best Paper Award
Cumulative step length
adaptation on ridge functions
Parallel Problem Solving from Nature — PPSN IX. Reykjavik, 2006.
D. V. Arnold and A. MacLeod
Hierarchically
organised evolution strategies on the parabolic ridge
Genetic and Evolutionary Computation Conference. Seattle, WA, 2006.
G. A. Jastrebski and D. V. Arnold
Improving evolution
strategies through active covariance matrix adaptation
IEEE Congress on Evolutionary Computation. Vancouver, 2006.
D. V. Arnold and D. MacDonald
Weighted
recombination evolution strategies on the parabolic ridge
IEEE Congress on Evolutionary Computation. Vancouver, 2006.
D. V. Arnold
Evolution strategies
with adaptively rescaled mutation vectors
IEEE Congress on Evolutionary Computation. Edinburgh, 2005.
D. V. Arnold
Optimal weighted
recombination
Foundations of Genetic Algorithms, 8. AizuWakamatsu, Japan, 2005.
D. V. Arnold
An analysis of
evolutionary gradient search
IEEE Congress on Evolutionary Computation. Portland, OR, 2004.
H.G. Beyer and D. V. Arnold
Best Paper Award, ES/EP Track
The steady state
behavior of (μ/μ,λ)ES on ellipsoidal fitness models
disturbed by noise
Genetic and Evolutionary Computation Conference. Chicago, IL, 2003.
D. V. Arnold and H.G. Beyer
On the effects
of outliers on evolutionary optimization
Intelligent Data Engineering and Automated Learning. Hong Kong, 2003.
D. V. Arnold and H.G. Beyer
Random dynamics
optimum tracking with evolution strategies
Parallel Problem Solving from Nature — PPSN VII. Granada, 2002.
D. V. Arnold and H.G. Beyer
Investigation of the
(μ,λ)ES in the presence of noise
IEEE Congress on Evolutionary Computation. Seoul, 2001.
S. Markon, D. V. Arnold, T. Bäck, T. Beielstein, and
H.G. Beyer
Thresholding — A
selection operator for noisy ES
IEEE Congress on Evolutionary Computation. Seoul, 2001.
D. V. Arnold and H.G. Beyer
Efficiency and
mutation strength adaptation of the (μ/μ,λ)ES in a noisy
environment
Parallel Problem Solving from Nature — PPSN VI. Paris, 2000.
D. V. Arnold and H.G. Beyer
Local
performance of the (μ/μ,λ)ES in a noisy
environment
Foundations of Genetic Algorithms 6. Charlottesville, VA, 2001.
H.G. Beyer and D. V. Arnold
Fitness noise and localization errors of the optimum in general quadratic
fitness models
Genetic and Evolutionary Computation Conference. Orlando, FL, 1999
R. F. Hadley, D. Arnold, and V. Cardei
Syntactic systematicity arising from semantic predictions in a
Hebbiancompetitive network
Conference of the Cognitive Science Society. Mahwah, NJ, 1998.
Theses
D. Arnold
Local Performance of Evolution Strategies in the Presence of Noise
Dissertation, Universität Dortmund, Fachbereich Informatik, 2001.
D. Arnold
Evolution of Legged Locomotion
M.Sc. Thesis, Simon Fraser University, School of Computing Science,
1997.
D. Arnold
Informationstheoretische Analyse von Phasenübergängen
Diplomarbeit, Universität Dortmund, Fachbereich Informatik, 1994.
