Nemati Mehrdad, Zandi Yousef, Sabouri Jamshid
Department of Civil Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran.
Sci Rep. 2024 Nov 9;14(1):27345. doi: 10.1038/s41598-024-79316-z.
Optimum design of truss structures can be a challenging and difficult field of study specially if an optimum design problem is comprised of continuous and discrete decision variables such as in truss size and layout optimization problems. Usually metaheuristic approaches are selected to solve these kind of problems and there are many different metaheuristic methods that have been used in dealing with truss optimization problems, which provide optimum solutions for those problems. However, among these various proposed metaheuristics, it is very seldom to face and find a method that is based on technologies such as computer networks. This paper aims to utilize a metaheuristic algorithm which is based on some principals of connected banking systems, which is called the Connected Banking System Optimizer(CBSO) algorithm. The performance of the CBSO is tested against three benchmark truss size/layout optimum design problems namely 15, 18 and 25 bar truss structures. Besides the truss size/layout problems, CEC-BC-2017 test functions with ten dimensions and also three other constrained optimum design problems are also investigated to examine the performance of the CBSO in dealing with these standard unconstrained and constrained test functions. The results of the CBSO optimum designs are presented and compared with some of the available studies in the literature. Statistical analyses are done to have a fair evaluation of the CBSO algorithm's efficiency and its ability in dealing with the benchmark truss size/layout optimization problems. The CBSO outperforms its rivals and presents lighter weight truss structures. There is no need for configuration of extra parameters in the CBSO algorithm when solving the examined benchmark truss structures, which makes it a robust parameter-free optimization algorithm.
桁架结构的优化设计可能是一个具有挑战性且困难的研究领域,特别是当一个优化设计问题由连续和离散的决策变量组成时,例如在桁架尺寸和布局优化问题中。通常会选择元启发式方法来解决这类问题,并且有许多不同的元启发式方法已被用于处理桁架优化问题,这些方法为这些问题提供了最优解。然而,在这些各种提出的元启发式方法中,很少遇到并找到一种基于计算机网络等技术的方法。本文旨在利用一种基于连接银行系统的一些原理的元启发式算法,即连接银行系统优化器(CBSO)算法。针对三个基准桁架尺寸/布局优化设计问题,即15杆、18杆和25杆桁架结构,对CBSO的性能进行了测试。除了桁架尺寸/布局问题外,还研究了具有十个维度的CEC - BC - 2017测试函数以及其他三个约束优化设计问题,以检验CBSO在处理这些标准无约束和约束测试函数方面的性能。给出了CBSO优化设计的结果,并与文献中的一些现有研究进行了比较。进行了统计分析,以公平评估CBSO算法的效率及其处理基准桁架尺寸/布局优化问题的能力。CBSO优于其竞争对手,并给出了更轻重量的桁架结构。在求解所研究的基准桁架结构时,CBSO算法无需配置额外的参数,这使其成为一种强大的无参数优化算法。