<span id="docs-internal-guid-a50ef6a8-7fff-b6d7-8e58-d434be6097d4"><span>This paper proposes a novel approach based on the NSCE (elitist non dominated sorting cross entropy), for optimization of location and size flexible AC transmission system device (FACTS) namely: unified power flow controller (UPFC) to achieve optimal reactive (ORPF). In present work, main objective is minimize ...

Machine learning techniques heavily rely on available training data in a set. Certain features the can interfere with process, so it is required to remove irrelevant and redundant build robust model. As such, several feature selection are usually applied pre-processing phase obtain most appropriate set of improve overall process. In this paper, new approach proposed based modified Teaching-Lear...

The paper deals with efficiency comparison of two global evolutionary optimization methods implemented in MATLAB. Attention is turned to an elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and a novel multi-objective Particle Swarm Optimization (PSO). The performance of optimizers is compared on three different test functions and on a cavity resonator synthesis. The microwave resonator...

This paper examines the evolutionary approach for aircraft design optimization. Several niching and elitist models are first applied to Multiple-Objective Genetic Algorithms (MOGAs). Numerical results suggest that the combination of the fitness sharing and the best-N selection leads to the best performance. The resulting MOGA is then applied to multidisciplinary design optimization problems of ...