Genetic algorithms are a robust adaptive optimization technique based on a biological paradigm. They perform efficient search on poorly-defined spaces by maintaining an ordered po...
A new stochastic method for locating the global minimum of a multidimensional function inside a rectangular hyperbox is presented. A sampling technique is employed that makes use ...
This paper proposes a hybrid genetic algorithm for multiple sequence alignment. The algorithm evolves guide sequences and aligns input sequences based on the guide sequences. It a...
This work studies the mGA operator (Micro Genetic Algorithm), that has been proposed in literature as a “local search” operator for optimization with Genetic Algorithm. A new ...
A hybrid Multi-Objective Evolutionary Algorithm is used to tackle the uncapacitated exam proximity problem. In this hybridization, local search operators are used instead of the tr...