References - Self-Adaptive Heuristics for Evolutionary Computation - page 155

124. Rudolph, G.: Convergence of evolutionary algorithms in general search spaces. In:
Proceedings of the Proceedings of the International Conference on Evolutionary
Computation, pp. 50-54 (1996)
125. Rudolph, G.: Finite Markov chain results in evolutionary computation: A tour
d'horizon. Fundamenta Informaticae 35(1-4), 67-89 (1998)
126. Rudolph, G.: Self-adaptive mutations lead to premature convergence. IEEE
Transactions on Evolutionary Computation 5(4), 410-414 (2001)
127. Schaffer, J.D., Caruana, R., Eshelman, L.J., Das, R.: A study of control parame-
ters affecting online performance of genetic algorithms for function optimization.
In: Proceedings of the 3rd International Conference on Genetic Algorithms - ICGA
1989, pp. 51-60 (1989)
128. Schaffer, J.D., Morishima, A.: An adaptive crossover distribution mechanism
for genetic algorithms. In: Proceedings of the 2nd International Conference on
Genetic Algorithms on Genetic algorithms and their application, pp. 36-40.
Lawrence Erlbaum Associates, Inc., Mahwah (1987)
129. Schoenauer, M., Michalewicz, Z.: Evolutionary computation at the edge of feasi-
bility. In: Voigt, H.-M., Ebeling, W., Rechenberg, I., Schwefel, H.-P. (eds.) PPSN
1996. LNCS, vol. 1141, pp. 245-254. Springer, Berlin (1996)
130. Schoenauer, M., Xanthakis, S.: Constrained GA optimization. In: Forrest, S. (ed.)
Proceedings of the 5th International Conference on Genetic Algorithms - ICGA
1993, pp. 573-580. Morgan Kaufman Publishers Inc., San Francisco (1993)
131. Schwefel, H.-P.: Kybernetische Evolution als Strategie der experimentellen
Forschung in der Stromungstechnik. diploma thesis, TU Berlin, Hermann
Fottinger-Institut fur Stromungstechnik (March 1965)
132. Schwefel, H.-P.: Adaptive Mechanismen in der biologischen Evolution und ihr
Einfluss auf die Evolutionsgeschwindigkeit. Interner Bericht der Arbeitsgruppe
Bionik und Evolutionstechnik am Institut fur Mess- und Regelungstechnik, TU
Berlin (July 1974)
133. Schwefel, H.-P.: Evolutionsstrategie und numerische Optimierung. PhD thesis,
TU Berlin (1975)
134. Schwefel, H.-P.: Numerische Optimierung von Computer-Modellen mittels der
Evolutions strategie. Birkhauser, Basel (1977)
135. Schwefel, H.-P.: Evolution and Optimum Seeking. In: Sixth-Generation Computer
Technology. Wiley Interscience, New York (1995)
136. Sebag, M., Ducoulombier, A.: Extending population-based incremental learning to
continuous search spaces. In: Eiben, A.E., Back, T., Schoenauer, M., Schwefel, H.-
P. (eds.) PPSN 1998. LNCS, vol. 1498, pp. 418-427. Springer, Heidelberg (1998)
137. Semenov, M.A., Terkel, D.A.: Analysis of convergence of an evolutionary al-
gorithm with self-adaptation using a stochastic lyapunov function. Evol. Com-
put. 11(4), 363-379 (2003)
138. Shapiro, J., Prugel-Bennett, A., Rattray, M.: A statistical mechanical formula-
tion of the dynamics of genetic algorithms. In: Evolutionary Computing, AISB
Workshop, pp. 17-27 (1994)
139. Shi, Y., Eberhart, R.: A modified particle swarm optimizer. In: Proceedings of
the International Conference on Evolutionary Computation, pp. 69-73 (1998)
140. Sinha, A., Srinivasan, A., Deb, K.: A population-based, parent centric procedure
for constrained real-parameter optimization. In: Yen, G.G., Lucas, S.M., Fogel,
G., Kendall, G., Salomon, R., Zhang, B.-T., Coello Coello, C.A., Runarsson, T.P.
(eds.) Proceedings of the 2006 IEEE Congress on Evolutionary Computation,
Vancouver, pp. 239-245. IEEE Press, Los Alamitos (2006)