Fitness functions derived for certain white-box test goals can cause problems for Evolutionary Testing (ET), due to a lack of sufficient guidance to the required test data. Often t...
Several inverse problems exist in the atmospheric sciences that are computationally costly when using traditional gradient based methods. Unfortunately, many standard evolutionary ...
Monte Lunacek, L. Darrell Whitley, Philip Gabriel,...
This paper presents an architecture which is suitable for a massive parallelization of the compact genetic algorithm. The approach is scalable, has low synchronization costs, and i...
This paper makes a number of connections between life and various facets of genetic and evolutionary algorithms research. Specifically, it addresses the topics of adaptation, mult...
A genetic algorithm has been developed in order to find the global minimum of platinum-palladium nanoalloy clusters. The effect of biasing the initial population and predating sp...
Abstract. Human-based genetic algorithms are powerful tools for organizational modeling. If we enhance them using chance discovery techniques, we obtain an innovative approach for ...
Genetic algorithms require relatively large computation time to solve optimization problems, especially in VLSI CAD such as module placement. Therefore, island-based parallel GAs a...