A particular steady-state strategy of evolution with a small sized population is studied in this paper. After comparison with GA and ES, we specially focus our attention on the choice of genetic operators, and the way to apply them. Knowing that it is not possible to reach a universal heuristic able to choose the genetic operators and to manage them, we present methods where the genetic operato...

Sequences of macromolecules have "signals" or patterns that arise from a number of sources, particularly from shared common history or phylogeny. We discuss methods for inferring evolutionary trees from these patterns or signals under five properties desired for an ideal method. These five desiderata are that the methods be efficient (fast), consistent, powerful, robust, and falsifiable. Our co...

Evolutionary Algorithms (EAs) have recently been successfully applied to numerical optimization problems. A major obstacle in the application of EAs has been the relatively slow convergence rate. This becomes more pronounced when the functions to be optimized become complex and numerically intensive. In this paper five different methods of speeding up EA convergence are reviewed. These include ...

The stock market has always been an attractive area for researchers since no method has been found yet to predict the stock price behavior precisely. Due to its high rate of uncertainty and volatility, it carries a higher risk than any other investment area, thus the stock price behavior is difficult to simulation. This paper presents a “data mining-based evolutionary fuzzy expert system” (DEFE...

Many real-world problems involve two types of problem difficulty: i) multiple, conflicting objectives and ii) a highly complex search space. On the one hand, instead of a single optimal solution competing goals give rise to a set of compromise solutions, generally denoted as Pareto-optimal. In the absence of preference information, none of the corresponding trade-offs can be said to be better t...

In recent years, artificial neural networks (ANNs) have been applied to many geotechnical engineering problems and have demonstrated some degree of success. In the majority of these applications, data division is carried out on an arbitrary basis. However, the way the data are divided can have a significant effect on model performance. In this report, the relationship between the statistical pr...

In this paper, we study the impact of selection methods in the context of on-line on-board distributed evolutionary algorithms. We propose a variant of the mEDEA algorithm in which we add a selection operator, and we apply it in a taskdriven scenario. We evaluate four selection methods that induce different intensity of selection pressure in a multi-robot navigation with obstacle avoidance task...

The experimental results reported in many papers suggest that making an appropriate a priori choice of an evolutionary method for a nonlinear parameter optimization problem remains an open question. It seems that the most promising approach at this stage of research is experimental, involving a design of a scalable test suite of constrained optimization problems, in which many features could be...

Modern fast primality testing uses a combination of Strong Probable Prime (SPRP) rejection tests. We find more powerful combinations by intensive search of the vast domain of SPRP test configurations. Evolutionary guidance using previous promising results boosts search speed. We implement the entire search on the GPU with the CUDA programming language resulting in 65-time speedup over a CPU sea...

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