Manually building neural network models is a great test of researchers’ knowledge reserves, so using Neural Architecture Search (NAS) to automatically construct networks becoming increasingly popular. This paper uses an improved Differentiable (DARTS) build classification model, DARTS gradient-based NAS algorithm. However, local selection, this proposes selection algorithm based on global selec...

The human has always been to find the best in all things. This Perfectionism has led to the creation of optimization methods. The goal of optimization is to determine the variables and find the best acceptable answer Due to the limitations of the problem, So that the objective function is minimum or maximum. One of the ways inaccurate optimization is meta-heuristics so that Inspired by nature, ...

Meta-heuristic algorithms inspired by the natural processes are part of the optimization algorithms that they have been considered in recent years, such as genetic algorithm, particle swarm optimization, ant colony optimization, Firefly algorithm. Recently, a new kind of evolutionary algorithm has been proposed that it is inspired by the human sociopolitical evolution process. This new algorith...

This paper aims at optimizing the parameters involved in stress analysis of perforated plates, in order to achieve the least amount of stress around the square-shaped holes located in a finite isotropic plate using metaheuristic optimization algorithms. Metaheuristics may be classified into three main classes: evolutionary, physics-based, and swarm intelligence algorithms. This research uses Ge...

in practice, obtaining the global optimum for the economic dispatch {bf (ed)}problem with ramp rate limits and prohibited operating zones is presents difficulties. this paper presents a new andefficient method for solving the economic dispatch problem with non-smooth cost functions using afuzzy adaptive genetic algorithm (faga). the proposed algorithm  deals  with the issue ofcontrolling the ex...