Exploration of the search space occurs at the cost of destructing existing good solutions. This cost will grow as the search progresses. The parametric uniform crossover is a general form of the uniform crossover operator. Using this operator, it would be possible to control the swapping probability of each locus. An adaptive method proposed that control the value of the exchange probability of...

In many Genetic Algorithms applications the objective is to nd a (near-)optimal solution using a limited amount of computation. Given these requirements it is diicult to nd a good balance between exploration and exploitation. Usually such a balance is found by tuning the various parameters (like the selective pressure, population size, the mutation-and crossover rate) of the Genetic Algorithm. ...

Geometric crossover is a representation-independent generalization of traditional crossover for binary strings. It is defined in a simple geometric way by using the distance associated with the search space. Many interesting recombination operators for the most frequently used representations are geometric crossovers under some suitable distance. Showing that a given recombination operator is a...

⎯The convergence of genetic algorithm is mainly determined by its core operation crossover operation. When the objective function is a multiple hump function, traditional genetic algorithms are easily trapped into local optimum, which is called premature convergence. In this paper, we propose a new genetic algorithm with improved arithmetic crossover operation based on gradient method. This cro...

In this paper, we propose simulated binary crossover with lognormal probability distribution (SBX-l), a new recombination operator for real-coded GAs. It is a parent-centric operator uses lognormal distribution for spread factor. SBX-l operator with rigid and flexible bound is proposed. Experimental results using test functions, which are commonly used in studies of evolutionary algorithms, are...

Different kinds of genetic algorithms have been investigated for a parameter identification of a fermentation process. Altogether eight realizations of genetic algorithms have been presented four of simple genetic algorithms and four of multi-population ones. Each of them is characterized with a different sequence of implementation of main genetic operators, namely selection, crossover and muta...

The exchange of a computer system’s components during operation can be accomplished by the so called Hot Swap technology. This technology makes it possible to continuously run a computer system without the necessity of a shutdown for maintenance purposes, e.g. upgrading of a network adapter. Thus the overall uptime of a system can be drastically increased. The Hot Swap capability has been integ...

0167-8655/$ see front matter 2012 Elsevier B.V. A http://dx.doi.org/10.1016/j.patrec.2012.06.017 ⇑ Corresponding author. Tel.: +358 132517962. E-mail address: [email protected] (Q. Zhao). Expectation maximization (EM) algorithm is a popular way to estimate the parameters of Gaussian mixture models. Unfortunately, its performance highly depends on the initialization. We propose a random swap EM...