this paper, presents a suitable control system to manage energy in distributed power generation system with a battery energy storage station and fuel cell. first, proper dynamic shape modeling is prepared. second, control system is proposed which is based on classic controller. this model is educated with genetic algorithm and particle swarm optimization. the proposed strategy is compared with ...

optimization of cutting conditions is a non-linear optimization with constraint and it is very important to the increase of productivity and the reduction of costs. in recent years, several evolutionary and meta-heuristic optimization algorithms were introduced. the cuckoo optimization algorithm (coa) is one of several recent and powerful meta-heuristics which is inspired by the cuckoos and the...

This paper presents a dynamic adaptation scheme for the frequency of inter-deme migration in distributed genetic algorithms (GA), and its VLSI hardware design. Distributed GA, or multi-deme-based GA, uses multiple populations which evolve concurrently. The purpose of dynamic adaptation is to improve convergence performance so as to obtain better solutions. Through simulation experiments, we pro...

Gibberellins (GAs) play many biological roles in higher plants. We collected and performed genetic analysis on rice (Oryza sativa) GA-related mutants, including GA-deficient and GA-insensitive mutants. Genetic analysis of the mutants revealed that rice GA-deficient mutations are not transmitted as Mendelian traits to the next generation following self-pollination of F1 heterozygous plants, alth...

We compare Genetic Algorithms (GA) with a functional search method, Very Fast Simulated Reannealing (VFSR), that not only is efficient in its search strategy, but also is statistically guaranteed to find the function optima. GA previously has been demonstrated to be competitive with other standard Boltzmann-type simulated annealing techniques. Presenting a suite of six standard test functions t...

This paper explores & reviews the use of genetic algorithms by various researchers as a solution to discover motifs in molecular sequences. This survey talks about the general GA based procedure for motif discovery & reviews the latest developments in DNA motif finding using Genetic algorithms. Although GA approach has not been applied extensively by researchers as compared to other computation...

A method for solving satisfiability (SAT) instances is presented. It is based on two basic components: An Epistasis Reducer Algorithm (ERA) and a simple Genetic Algorithm (GA). ERA is implemented by a simulated annealing algorithm (SA), which preprocess the original SAT problem by rearranging the variables to satisfy the condition that the most related ones are in closer positions inside the ch...

This paper addresses an attempt to evolve genetic algorithms by a particular genetic programming method to make it able to solve the classical Job Shop Scheduling problem (JSSP), which is a type of very well known hard combinatorial optimisation problems. The aim is to look for a better GA such that solves JSSP with preferable scores. This looking up procedure is done by evolving GA with GP. Fi...

This paper proposes genetic algorithms (GAs) for path planning and trajectory planning of an autonomous mobile robot. Our GA-based approach has an advantage of adaptivity such that the GAs work even if an environment is time-varying or unknown. Therefore, it is suitable for both off-line and on-line motion planning. We first presents a GA for path planning in a 2D terrain. Simulation results on...

In this paper an accurate method is presented for determining of the device sizes in a RF circuit based on genetic algorithm (GA). HSPICE RF simulation is used for evaluating of the fitness of the circuit specifications per every iteration of the GA. Also an example for a LNA is presented for evaluating of non-dominated sorting genetic algorithm (NSGA-II) as a method of multi objective genetic ...