Abstract. In this paper we give a representation-independent topological definition of crossover that links it tightly to the notion of fitness landscape. Building around this defi...
A genetic algorithm for the longest common subsequence problem encodes candidate sequences as binary strings that indicate subsequences of the shortest or first string. Its fitnes...
—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...
In this paper, a new gene based adaptive mutation scheme is proposed for genetic algorithms (GAs), where the information on gene based fitness statistics and on gene based allele...
This paper presents an Adaptive Genetic Algorithm (AGA) where selection pressure, crossover and mutation probabilities are adapted according to population diversity statistics. Th...