Sensitivity Analysis of a Species Conserving Genetic Algorithm's Parameters for Addressing the Niche Radius Problem

Niche Genetic Algorithms (NGA) are a special category of Genetic Algorithms (GA) that solve problems with multiple optima. These algorithms preserve genetic diversity and prevent the GA from converging on a single optima. Many NGAs suffer from the Niche Radius Problem (NRP), which is the problem of correctly setting a radius parameter for optimal results. While the selection of the radius value has been widely researched, the effects of other GA parameters on genetic diversity is not well known. This research is a parameter sensitivity analysis on the other parameters in a GA, namely mutation rate, number of individuals and number of generations.

Niche Genetic Algorithms are better than traditional Genetic Algorithms for de novo Protein Folding

Here we demonstrate that Niche Genetic Algorithms (NGA) are better at computing de novo protein folding than traditional Genetic Algorithms (GA). Previous research has shown that proteins can fold into their active forms in a limited number of ways; however, predicting how a set of amino acids will fold starting from the primary structure is still a mystery. GAs have a unique ability to solve these types of scientific problems because of their computational efficiency. Unfortunately, GAs are generally quite poor at solving problems with multiple optima. However, there is a special group of GAs called Niche Genetic Algorithms (NGA) that are quite good at solving problems with multiple optima. In this study, we use a specific NGA: the Dynamic-radius Species-conserving Genetic Algorithm (DSGA), and show that DSGA is very adept at predicting the folded state of proteins, and that DSGA is better than a traditional GA in deriving the correct folding pattern of a protein.

Research on Satellite Formation Establishing in Elliptical Orbits Based on Two-Impulse Control

In order to solving the establishment problem of satellites formation establishing in elliptical orbits, the problem of Lambert transfer based on two-impulse control with unfixed time and initial position is studied. The Niche Genetic Algorithms (NGA) is used to locating the optimal transfer orbit, and the transfer time and initial position are coded into genetic algorithms, as well as the fitness functions are designed to total coasting. The results show that the NGA can solve the optimization problem of two-impulse control effectively, furthermore, the performance of NGA is more effective than the traditional genetic algorithm. The research provides a way for satellites formation establishing based on two-impulse control.

Optimized Analysis of the Hollow Floor Based on the Niche Genetic Algorithms

Nowadays, the hollow floor is widely used due to its excellent mechanical property and economic benefit.However, its related specification is absence of evaluation in geometric parameters. The optimized analysis aimed at the hollow floor under vertical load, the total cost of the hollow floor is considered as a objective function, the maximum deflection and the threshold value of the geometric parameters are considered as constrain conditions. The program, which introduces the section design and compiled by the python script, based on the niche genetic algorithms is used to analyze the optimization of a hollow floor. Comparing to the global optimal solution, the program achieves good results. It indicates that the niche genetic algorithms is efficient and suited for the optimization analysis of hollow floor. The above mentioned conclusions will be conducive to engineering design and further research in this field.

Study on Hull Form Optimization for Minimum Resistance Based on Niche Genetic Algorithms

The Niche Genetic Algorithms (NGAs) can overcome the deficiency of Genetic Algo-rithms (GAs), such as premature convergence and low ability of local search. The NGA can maintain the diversity of the individual in groups. Meanwhile, it has a high ability of globally searching and a rapid convergence rate. To get the hull form with minimum resistance, an optimization design of the hull form with NGA method, which is combined with CAD technology based on the Rankine source method, is proposed. The total resistance is taken as objective function in the optimization process, study on the optimization of the fore-body of hull is proposed, with the parameter of hull form modification function as design variables, with an appropriate displacement as the basic constraint. Initially, the Series60 hull was selected as the base for the optimized calculation. Comparison between the optimized results of the NGAs and GAs shows that the hull based on the optimized NGA are valid and effective.