Optimization is an important fields of study in science where researchers seek to make the best and most practical decisions. Solving real optimization problems is an intractable issue which calls for generating an approximate using meta-heuristic algorithms. This study proposes a meta-heuristic...

Optimization, which, by definition, can help one find the best solution from all feasible solutions, has sometimes been an interesting and important area for research in science. Solving real and hard optimization problems calls for developing approximate, heuristic, and meta-heuristic...

In this article, a type of bivariate rational interpolation function is constructed for preserving image texture structure, which integrates polynomial functions with a rational function. On the basis of this model, an image interpolation algorithm for texture preserving is proposed. First, an...

Antennas are considered as a significant component in any wireless system. There are numerous factors and constraints that affect its design. Therefore, recently several algorithms are developed to allow the designers optimize the antenna with respect to numerous different criteria, general...

The Gauss-Marquardt-Levenberg (GML) method of computer-based parameter estimation, in common with other gradient-based approaches, suffers from the drawback that it may become trapped in local objective function minima, and thus report optimized parameter values that are not, in fact, optimized...