Gene expression data are usually redundant, and only a subset of them presents distinct profiles for different classes of samples. Thus, selecting high discriminative genes from gene expression data has become increasingly interesting in bioinformatics. In this paper, a multiobjective binary differential evolution method (MOBDE) is proposed to select a small subset of informative genes relevant...

It is well-known that, given inorder traversal along with one of the preorder or postorder traversals of a binary tree, the tree can be determined uniquely. Several algorithms have been proposed to reconstruct a binary tree from its inorder and preorder traversals. There is one study to reconstruct a binary tree from its inorder and postorder traversals, and this algorithm takes running time of...

The shape optimization of gravity dam is posed as an optimization problem with goals of minimum value of concrete, stresses and maximum safety against overturning and sliding need to be achieved. Optimally designed structure generally saves large investments especially for a large structure. The size of hydraulic structures is usually huge and thus requires a huge investment. If the optimizatio...

Electronic hardware’s demandsthat the simple in architecture, power consumption, speed in operation and should be automatically regenerating the program if the program is failure. Genetic algorithm is one of the evolutionary algorithms. Using evolutionary algorithm we can get the desired program automatically. FPGA configuration bits are perfectly matches with binary bits of evolvable hardware....

In this paper a new evolutionary paradigm is proposed. A technique called Adaptive Representation Evolutionary Algorithm (AREA) based on this paradigm is designed. AREA involves dynamic alphabets for encoding solutions. Proposed adaptive representation is more compact than binary representation. Mutation is the unique variation operator. Mutations are usually more aggressive when higher alphabe...

the multivariate exponentially weighted moving average (mewma) control chart is one of the best statistical control chart that are usually used to detect simultaneous small deviations on the mean of more than one cross-correlated quality characteristics. the economic design of mewma control charts involves solving a combinatorial optimization model that is composed of a nonlinear cost function ...

evolutionary algorithms are some of the most crucial random approaches tosolve the problems, but sometimes generate low quality solutions. on the otherhand, learning automata are adaptive decision-making devices, operating onunknown random environments, so it seems that if evolutionary and learningautomaton based algorithms are operated simultaneously, the quality of results willincrease sharpl...

This study proposes a new self-adaptive binary variant of a differential evolution algorithm, based on measure of dissimilarity and named SabDE. It uses an adaptive mechanism for selecting how new trial solutions are generated, and a chaotic process for adapting parameter values. SabDE is compared against a number of existing state of the art algorithms, on a set of benchmark problems including...

The main objective of this research is to automatically design Artificial Neural Network models with sigmoid basis units for multiclassification tasks in predictive microbiology. The classifiers obtained achieve a double objective: a high classification level in the dataset and high classification levels for each class. The Memetic Pareto Differential Evolution Neural Network chosen to learn th...

Due to the resource constraint and dynamic parameters, reducing energy consumption became the most important issues of wireless sensor networks topology design. All proposed hierarchy methods cluster a WSN in different cluster layers in one step of evolutionary algorithm usage with complicated parameters which may lead to reducing efficiency and performance. In fact, in WSNs topology, increasin...