Genetic algorithms are widely used as optimization and adaptation tools, and they became important in artiicial intelligence. Even though several successful applications have been reported, recent research has identiied some ineeciencies in genetic algorithm performance. This paper argues that the degradation of genetic algorithm performance originates from the random application of the variati...

A method for calculating genetic drift in terms of changing population fitness variance is presented. The method allows for an easy comparison of different selection schemes and exact analytical results are derived for traditional generational selection, steady-state selection with varying generation gap, a simple model of Eshelman’s CHC algorithm, and (μ + λ) evolution strategies. The effects ...

In this paper, an improved genetic algorithm for multi-object optimization is proposed. Simulated annealing is used to local search in genetic algorithms. Furthermore, fuzzy reasoning is adopted to modify crossover probability and mutation probability according to characteristics of population in genetic algorithms instead of fixed parameters. And so, it can be convergence to global optimum qui...

In this paper, a genetic algorithm with minimum description length (GAWMDL) is proposed for grammatical inference. The primary challenge of identifying a language of infinite cardinality from a finite set of examples should know when to generalize and specialize the training data. The minimum description length principle that has been incorporated addresses this issue is discussed in this paper...

The problem of Dynamic Job Shop (DJS) scheduling is one of the most complex problems of machine scheduling. This problem is one of NP-Hard problems for solving which numerous heuristic and metaheuristic methods have so far been presented. Genetic Algorithms (GA) are one of these methods which are successfully applied to these problems. In these approaches, of course, better quality of solutions...

Resumen. Database schemas and user queries are continuously growing with the need for storing and accessing large amounts of structured information. Among the several proposals to deal with the Large Join Query Problem, genetic optimizers have been shown to be a competitive approach. We propose a new search strategy to improve the quality and convergence of genetic query optimizers. We call our...

A data mining procedure for automatic determination of fuzzy decision tree structure using a genetic program (GP) is discussed. A GP is an algorithm that evolves other algorithms or mathematical expressions. Innovative methods for accelerating convergence of the data mining procedure and reducing bloat are given. In genetic programming, bloat refers to excessive tree growth. It has been observe...