This paper presents a novel metaheuristic optimization algorithm inspired by the geometrical features of circles, called circle search (CSA). The is most well-known geometric object, with various including diameter, center, perimeter, and tangent lines. ratio between radius line segment orthogonal function angle opposite to radius. plays an important role in exploration exploitation behavior CS...

The work is devoted to solving the problem of topological optimization in design lightweight structures. advantages and disadvantages popular methods are analyzed. One characteristic problems all dependence their results on grid partitioning. Besides, there a necessity recast geometry model structure. To solve this problem, it proposed perform formation cavities based ESO method directly at con...

Purpose: This study aims to examine the interaction between process parameters and bead geometry, to perform the research to predict optimal bead geometry (bead width, reinforcement height, left leg length, right leg length) through the analysis of experimental data. For this, not only linear and the curvilinear equations were developed to predict bead geometry, but also interactions between pr...

A rapid geometry engine (RAGE) has been developed to allow for preliminary design analysis without labor-intensive CAD support. The geometry tool builds complex aircraft configurations using a component-based approach. Basic algorithms for creating the primary components are presented and discussed. Examples of many widely varying geometry models are shown. A select geometry model is analyzed w...

This paper presents and compares methods of error metrics used to measure the error for the flank milling of a machined ruled surface. The aim of this work is to propose a new scheme for error approximation that is easy to implement and gives better error assessment when using optimization techniques to determine tool position. We propose using as the error calculation an approximation to the d...

Optimization on manifolds is a rapidly developing branch of nonlinear optimization. Its focus is on problems where the smooth geometry of the search space can be leveraged to design efficient numerical algorithms. In particular, optimization on manifolds is wellsuited to deal with rank and orthogonality constraints. Such structured constraints appear pervasively in machine learning applications...

We have applied an optimization method in conjunction with numerical simulations to minimize the mixing time of a microfluidic mixer developed for protein folding studies. The optimization method uses a semideterministic algorithm to find the global minimum of the mixing time by varying the mixer geometry and flow conditions. We describe the minimization problem and constraints and give a brief...