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== Reference ==
C. Wellock and [[Brian J. Ross]]: [[An Examination of Lamarckian Genetic Algorithms]]. GECCO-2001 Late-breaking papers, pp.474-481.

== DOI ==

== Abstract ==
In keeping with the spirit of Lamarckian
evolution, variations on a simple genetic
algorithm are compared, in which each
individual is optimized prior to evaluation. Four
different optimization techniques in all are
tested: random hillclimbing, social (memetic)
exchange, and two techniques using artificial
neural nets (ANNs). These techniques are tested
on a set of three sample problems: an instance of
a minimum-spanning tree problem, an instance
of a travelling salesman problem, and a problem
where ANNs are evolved to generate a random
sequence of bits. The results suggest that in
general, social exchange provides the best
performance, consistently outperforming the
non-optimized genetic algorithm; results for
other optimization techniques are less
compelling.

== Extended Abstract ==

== Bibtex ==

== Used References ==
Ackley, D. H. & Littman, M. L. A Case for Lamarckian
Evolution. (1994). In C. G. Langton (Ed.), Artificial Life
III. (pp. 3-11). Reading, MA: Addison-Wesley.

Arora, Sanjeev. Polynomial time approximation schemes
for Euclidean TSP and other geometric problems. (1996).
In Proceedings of the 37th Annual IEEE Symposium on
Foundations of Computer Science. (pp. 2-12).

Burkhardt, Richard W., Jr. (1977). The Sprit of System.
Cambridge, MA: Harvard University Press.

Cheng, R. & Gen, M. (1997). Parallel Machine
Scheduling Problems Using Memetic Algorithms.
Computers & Industrial Engineering, 33(3-4), 761-764.

Cheng, R., Gen, M., & Tsujimura, Y. (1999). A tutorial
survey of job-shop scheduling problems using genetic
algorithms, part II: hybrid genetic search strategies.
Computers & Industrial Engineering, 36, 343-364.

Darwin, Charles. (1859) . On the Origin of Species by
Means of Natural Selection. London: J. Murray.

Dozier, G., Bowen, J., & Homaifar, A. (1998). Solving
Constraint Satisfaction Problems Using Hybrid
Evolutionary Search. IEEE Transactions on Evolutionary
Computation, 2(1), 23-32.

Gen, M., Ida, K. & Li, Y. (1998). Bicriteria
Transportation Problem by Hybrid Genetic Algorithm.
Computers & Industrial Engineering, 35(1-2), 363-366.

Grefenstette, J. Lamarckian Learning in Multi-agent
Environments. (1991). In Proceedings of the Fourth
International Conference on Genetic Algorithms. (pp.
303-310). San Mateo, CA: Morgan Kaufmann.

Grimaldi, R. (1994). Discrete and Combinatorial
Mathematics. Reading, MA: Addison-Wesley.

Han, J., Moraga, C., & Sinne, S. (1996). Optimization of
Feedforward Neural Networks. Engineering Applications
of Artificial Intelligence, 9(2), 109-119.

Hart, W. E., & Belew, R. K.. Optimization with Genetic
Algorithm Hybrids that Use Local Search. (1996). In R.K.
Belew & M. Mitchell (Eds.), Adaptive Individuals in
Evolving Populations. (pp. 483-496). Reading, MA:
Addison-Wesley.

Hinton, G. E. & Nowlan, S. J. How Learning Can Guide
Evolution. (1996). In R. K. Belew & M. Mitchell (Eds.),
Adaptive Individuals in Evolving Populations. (pp. 447-
457). Reading, MA: Addison-Wesley.

Katayama, K., Sakamoto, H. & Narihisa, H. (2000). The
Efficiency of Hybrid Mutation Genetic Algorithm for the
Travelling Salesman Problem. Mathematical and
Computer Modelling, 31, 197-203.

Kim, K. & Han, I. (2000). Genetic algorithms approach to
feature discretization in artificial neural networks for the
prediction of stock price index. Expert Systems with
Applications, 19, 125-132.

Knuth, Donald. (1969). The Art of Computer
Programming, vol. 2. Reading, MA: Addison-Wesley.

Koza, J. R. (1992). Genetic Programming: On the
Programming of Computers by Means of Natural
Selection. Reading, MA: MIT Press.

Lamarck, Jean-Baptiste. (1801). Système des animaux
sans vertèbres. Paris.

Li, Y., Tan, K. C., & Gong, M. Model reduction in
control systems by means of global structure evolution
and local parameter learning. (1996). In D. Dasgupta & Z.
Michaelwicz (Eds.), Evolutionary Algorithms in
Engineering Applications. New York: Springer-Verlag.

Mitchell, Melanie. (1996). An Introduction to Genetic
Algorithms. Cambridge, MA: MIT Press.

Pinker, S. (1997). How the Mind Works. New York: W.
W. Norton & Co.

Watson, M. (1997). Intelligent Java Applications for the
Internet and Intranets. San Francisco: Morgan Kaufmann
Publishers.

Whitley, D., Gordon, V. S., & Mathias, K. Lamarckian
Evolution, the Baldwin Effect and Function Optimization.
(1994). In Y. Davidor et al. (Eds.), Parallel Problem
Solving From Nature, vol. 3. (pp. 6-15). New York:
Springer-Verlag.

== Links ==
=== Full Text ===
http://www.cosc.brocku.ca/~bross/research/gecco_2001_lbp.pdf

[[intern file]]

=== Sonstige Links ===

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