In order to overcome the low convergence speed and prematurity of classical genetic algorithm, an improved method named directional self-learning of genetic algorithm (DSLGA) is p...
- Besides the difficulty of the application problem to be solved with Genetic Algorithms (GAs), an additional difficulty arises because the quality of the solution found, or the ...
—Inspired by the contours in topography, this paper proposes a contour method for the population-based stochastic algorithms to solve the problems with continuous variables. Rely...
This work presents a new approach to solve the location management problem by using the location areas approach. A combination of a genetic algorithm and the Hopfield neural netwo...
In this paper, we introduce a new genetic representation -- a splicing/decomposable (S/D) binary encoding, which was proposed based on some theoretical guidance and existing recom...