Modern synchrotron light source storage rings, such as the Swiss Light Source upgrade (SLS 2.0), use multibend achromats in their arc segments to achieve unprecedented brilliance. This performance comes at cost of increased focusing requirements, which turn require stronger sextupole and higher-order multipole fields for compensation effects on particles with energy deviation lead a considerabl...

In the field of multiobjective optimization, important efforts have been made in recent years to generate global Pareto fronts uniformly distributed. A new multiobjective evolutionary algorithm, called ↗−MOGA, has been designed to converge towards ΘP , a reduced but well distributed representation of the Pareto set ΘP . The algorithm achieves good convergence and distribution of the Pareto fron...

Reliability-based robust design optimization (RBRDO) is one of the most important tools developed in recent years to improve both quality and reliability of the products at an early design stage. This paper presents a comparative study of different formulation approaches of RBRDO models and their performances. The paper also proposes an evolutionary multi-objective genetic algorithm (MOGA) to o...

In this paper, a new genetic algorithm for multi-objective optimization problems is introduced. That is called “Local Cultivation GA (LCGA)”. LCGA has a neighborhood crossover mechanism in addition to the mechanism of GAs that had proposed in the past researches. As compared with SPEA2, NSGA-II, and MOGA, LCGA is the robust algorithm which should find the Pareto optimum solution. Since LCGA is ...

Analysis and interpretation of DNA Microarray data is a fundamental task in bioinformatics. Feature Extraction plays a critical role in better performance of the classifier. We address the dimension reduction of DNA features in which relevant features are extracted among thousands of irrelevant ones through dimensionality reduction. This enhances the speed and accuracy of the classifiers. Princ...

When performing search using Multiple Objective Genetic Algorithms (MOGAs) the aim is to maintain a diverse range of solutions whilst trying to converge these solutions onto the trade-off surface. In this paper a method to focus a MOGA search onto specific areas of this trade-off surface is investigated. Using interaction with a designer or decision maker his general preferences can be captured...