This paper calculates new bounds on the size of the performance gap between random codes and the best possible codes. The first result shows that, for large block sizes, the ratio of the error probability of a random code to the sphere-packing lower bound on the error probability of every code on the binary symmetric channel (BSC) is small for a wide range of useful crossover probabilities. Thu...

In this paper, I present the theoretical results obtained for Bentley’s genetic algorithm, which is used in CAD system to generate 3D-solids designs. The Vose-like-Markov-chain model for the Bentley’s GA is proposed. The transition matrices are found and the ergodity of the Markov chain and the asymptotic correctness in the probabilistic sense are shown by using the model. The microscopic Exact...

abstract background: menthol is the most important active material in mint and different mechanisms have been suggested for the way mint functions, most of which emphasize its analgesic effect owing to the presence of a group of temporary protein receptors. this study investigates the efficacy of peppermint capsule in the treatment of primary dysmenorrhea, in comparison with mefenamic acid and ...

An improved adaptive Genetic Algorithm was proposed, and the method was applied to the optimization process of tile image registration. This paper improved traditional Genetic Algorithm in three aspects. The probability of crossover and mutation was adjusted in a dynamic way according to the change of the fitness of individual during the evolutionary process and in different way when the evolut...

A genetic algorithm is one of a class of algorithms that searches a solution space for the optimal solution to a problem. First part of this work consists of basic information about Genetic algorithm like what are Individual, Population, Crossover, Genes, Binary Encoding, Flipping, Crossover probability, Mutation probability. What is it used for, what is their aim. In this article the methods o...

a r t i c l e i n f o a b s t r a c t Keywords: Uniform crossover Bit-flip mutation Walsh decomposition Landscape theory Fitness landscapes Uniform crossover and bit-flip mutation are two popular operators used in genetic algorithms to generate new solutions in an iteration of the algorithm when the solutions are represented by binary strings. We use the Walsh decomposition of pseudo-Boolean fu...

In this paper a new, general and exact schema theory for genetic programming is presented. The theory includes a microscopic schema theorem applicable to crossover operators which replace a subtree in one parent with a subtree from the other parent to produce the offspring. A more macroscopic schema theorem is also provided which is valid for crossover operators in which the probability of sele...

Many engineering optimization problems have not standard mathematical techniques, and cannot be solved using exact algorithms. Evolutionary algorithms have been successfully used for solving such optimization problems. Differential evolution is a simple and efficient population-based evolutionary algorithm for global optimization, which has been applied in many real world engineering applicatio...

A genetic algorithm is one of a class of algorithms that searches a solution space for the optimal solution to a problem. First part of this work consists of basic information about Genetic algorithm like what are Individual, Population, Crossover, Genes, Binary Encoding, Flipping, Crossover probability, Mutation probability. What is it used for, what is their aim. In this article the methods o...

Distributed generation (DG) systems are integral parts in future distribution networks. In this paper, a novel approach integrating crisscross optimization algorithm and Monte Carlo simulation (CSO-MCS) is implemented to solve the optimal DG allocation (ODGA) problem. The feature of applying CSO to address the ODGA problem lies in three interacting operators, namely horizontal crossover, vertic...