We present four abstract evolutionary algorithms for multi-objective optimization and
theoretical results that characterize their convergence behavior. Thanks to these results it is …

The inverse problem of groundwater flow is treated with an automatic method that can
produce several alternative solutions at once. During their joint optimization, these solutions …

Evolutionary algorithms (EAs) are random optimization methods inspired by genetics and
natural selection, resembling simulated annealing. We develop a method that can be used …

Evolutionary Algorithms, also known as Genetic Algorithms in a former terminology, are
probabilistic algorithms for optimization, which mimic operators from natural selection and …

Adaptive evolutionary algorithms require a more sophisticated modeling than their static-
parameter counterparts. Taking into account the current population is not enough when …

Genetic algorithms are sometimes disparagingly denoted as just a fancier form of a plain,
stupid heuristic. One of the main reasons for this kind of critique is that users believed a GA …

An Indexed Bibliography of Genetic Algorithms Theory and Comparisons Page 1 An Indexed
Bibliography of Genetic Algorithms Theory and Comparisons compiled by Jarmo T. Alander …

An Indexed Bibliography of Genetic Algorithm Implementations Page 1 An Indexed Bibliography
of Genetic Algorithm Implementations compiled by Jarmo T. Alander Department of Electrical …

An Indexed Bibliography of Genetic Algorithms in the Mediterranean Page 1 An Indexed
Bibliography of Genetic Algorithms in the Mediterranean compiled by Jarmo T. Alander …

The paper presents a new mathematical analysis of genetic algorithms (GAs); we propose
the use of random systems with complete connections (RSCC), a non-trivial extension of the …