Evolutionary Testing (ET) has been shown to be very successful in testing real world applications [16]. However, it has been pointed out [11], that further research is necessary if...
Many-objective problems are difficult to solve using conventional multi-objective evolutionary algorithms (MOEAs) as these algorithms rely primarily on Pareto ranking to guide the ...
Background: The selection of genes that discriminate disease classes from microarray data is widely used for the identification of diagnostic biomarkers. Although various gene sel...
This paper discusses a simple representation of variable-dimensional optimization problems for evolutionary algorithms. Although it was successfully applied to the optimization of ...
— Hybrid intelligent systems (HIS) are very successful in tackling problems comprising of more than one distinct computational subtask. For instance, decision-making problems are...