At present, the evolution cryptanalysis methods mainly adopt the basic genetic algorithm (literature [1] and [2]) which has ”early” phenomenon, searching stagnation in the near optimal solution, and low calculation efficiency. This paper inspired by biological genetic evolution proposes a niche genetic algorithm based on the code analysis method. This algorithm can keep the population diversity...

This paper presents a new generic Evolutionary Algorithm (EA) for retarding the unwanted effects of premature convergence. This is accomplished by a combination of interacting methods. To be intent on this a new selection scheme is introduced, which is designed to maintain the genetic diversity within the population by advantageous self-adaptive steering of selection pressure. Additionally this...

The objective of the present study was to estimate heritability values for some performance and egg quality traits of native fowl in Isfahan breeding center using REML and Bayesian approaches. The records were about 51521 and 975 for performance and egg quality traits, respectively. At the first step, variance components were estimated for body weight at hatch (BW0), body weight at 8 weeks of a...

Image registration is a useful technique for medical diagnosis and treatment. However,using basic genetic algorithm as similarity metric in medical image registration has some shortcomings,such as low efficiency and premature convergence that may lead to fail in medical image registration. This paper aims to provide an improved genetic algorithm on which such problems could be settled.Operation...

In this paper, an immune genetic based algorithm (IGA) for random test pattern generation was proposed. Genetic algorithms (GA) solve many search and optimization problems, effectively. However, they may drop into local optimal solutions; or they may find the optimal solution by low convergence speed. To overcome these problems, we used the immune concept and GA algorithm for random-based test ...

Distribution network reconfiguration is an important aspect of automation and optimization of distribution network system. To handle massive binary code infeasible solutions in distribution network reconfiguration, a kind of sequence code is presented in which a loop is a gene and the label of each switch in the loop is the gene value. To solve mutation probability and slow the convergence of c...

The global optimization of sensor locations for structural health monitoring systems is studied in this paper. First, the performance function based on damage detection is presented. Then, genetic algorithms (GAs) are adopted to search for the optimal locations of sensors. However, the simple GAs can result in infeasible solutions to the problem. Some improved strategies are presented in this p...

Differential Evolution (DE) algorithm is a new heuristic approach mainly having three advantages; finding the true global minimum regardless of the initial parameter values, fast convergence, and using few control parameters. DE algorithm is a population based algorithm like genetic algorithms using similar operators; crossover, mutation and selection. In this work, we have compared the perform...