Parallel genetic algorithms (PGAs) have been developed to reduce the large execution times that are associated with serial genetic algorithms (SGAs). They have also been used to s...
Lee Wang, Anthony A. Maciejewski, Howard Jay Siege...
X-ray spectroscopic analysis is a powerful tool for plasma diagnostics. We use genetic algorithms to automatically analyze experimental X-ray line spectra and discuss a particular...
Igor E. Golovkin, Roberto C. Mancini, Sushil J. Lo...
In this paper we present a method based on preference relations for transforming non–crisp (qualitative) relationships between objectives in multi–objective optimisation into ...
: This paper presents a genetic algorithm based approach for algebraic optimization of behavioral system specifications. We introduce a chromosomal representation of data-flow gr...
: This paper describes a rather novel method for the supervised training of regression systems that can be an alternative to feedforward Artificial Neural Networks (ANNs) trained w...
Mark J. Embrechts, Dirk Devogelaere, Marcel Rijcka...
We describe a genetic segmentation algorithm for video. This algorithm operates on segments of a string representation. It is similar to both classical genetic algorithms that ope...
Patrick Chiu, Andreas Girgensohn, Wolfgang Polak, ...
This paper looks upon the standard genetic algorithm as an artificial self-organizing process. With the purpose to provide concepts that make the algorithm more open for scalabili...
: One of the most important problems in SOC platforms design is that of defining strategies for tuning the parameters of a parameterized system so as to obtain the Pareto-optimal s...
Abstract. This work describes the use of genetic algorithms for automating the photogrammetric network design process. When planning a photogrammetric network, the cameras should b...
Automatic design of software architecture by use of genetic algorithms has already been shown to be feasible. A natural problem is to augment – if not replace – genetic algori...