Abstract

In this paper, the k-median of a graph is used to decompose the domain (mesh) of the continuous two- and three-dimensional finite element models. The problem of k-median is stated as an optimization problem and is solved by utilizing eight robust meta-heuristic algorithms. The Artificial Bee Colony algorithm (ABC), Cyclical Parthenogenesis algorithm (CPA), Cuckoo Search algorithm (CS), Teaching-Learning Based Optimization algorithm (TLBO), Tug of War Optimization algorithm (TWO), Water Evaporation Optimization algorithm (WEO), Ray Optimization algorithm (RO), and Vibrating Particles System algorithm (VPS) constitute the set of algorithms that are employed in the present study. In order to tune the parameters of the meta-heuristics, the Taguchi method is used. The efficiency and robustness of the algorithms are investigated through two- and three- dimensional finite element models.

摘要

在本文中，图的k中值用于分解连续二维和三维有限元模型的域（网格）。k的问题-median 被描述为一个优化问题，并通过使用八种鲁棒的元启发式算法来解决。人工蜂群算法 (ABC)、循环孤雌生殖算法 (CPA)、布谷鸟搜索算法 (CS)、基于教学的优化算法 (TLBO)、拔河优化算法 (TWO)、水蒸发优化算法 (WEO)、射线优化算法 (RO) 和振动粒子系统算法 (VPS) 构成了本研究中使用的一组算法。为了调整元启发式的参数，使用了田口方法。通过二维和三维有限元模型研究算法的效率和鲁棒性。