Intelligent multi-rebar layouts in precast concrete components using multi-agent coordination and particle swarm optimization

IF 7.5 1区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Expert Systems with Applications Pub Date : 2024-11-23 DOI:10.1016/j.eswa.2024.125896

Chengran Xu , Xiaolei Zheng , Jiepeng Liu , Weibing Peng , Kai Jiang , Chao Zhang , Zhou Wu

{"title":"Intelligent multi-rebar layouts in precast concrete components using multi-agent coordination and particle swarm optimization","authors":"Chengran Xu , Xiaolei Zheng , Jiepeng Liu , Weibing Peng , Kai Jiang , Chao Zhang , Zhou Wu","doi":"10.1016/j.eswa.2024.125896","DOIUrl":null,"url":null,"abstract":"<div><div>For precast concrete (PC) components, product-oriented design plays a vital role to achieve the industrial production and lean construction. Rebar collisions occur more frequently in PC components due to the irregular concrete profile and the numerous embedded parts. This paper presents an automated detailed design framework for PC components to generate the multi-rebar collision-free layout. Inspired by the formation moving capability of multi-agent flock, a multi-rebar layout module is developed to avoid rebar collision and uneven spacing. An integrated multi-agent coordination strategy is proposed for the multi-layout module, which includes three subtasks: virtual leader path planning, obstacle avoidance for collided agents, and formation optimization of agent flock. An optimization model is formulated to adjust multi-agent formation and particle swarm optimization (PSO) algorithm is employed to find the optimal solution. The developed framework is applied to the detailed design of a PC stair to demonstrate its practicability and efficiency.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"264 ","pages":"Article 125896"},"PeriodicalIF":7.5000,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Expert Systems with Applications","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0957417424027635","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}

引用次数: 0

Abstract

For precast concrete (PC) components, product-oriented design plays a vital role to achieve the industrial production and lean construction. Rebar collisions occur more frequently in PC components due to the irregular concrete profile and the numerous embedded parts. This paper presents an automated detailed design framework for PC components to generate the multi-rebar collision-free layout. Inspired by the formation moving capability of multi-agent flock, a multi-rebar layout module is developed to avoid rebar collision and uneven spacing. An integrated multi-agent coordination strategy is proposed for the multi-layout module, which includes three subtasks: virtual leader path planning, obstacle avoidance for collided agents, and formation optimization of agent flock. An optimization model is formulated to adjust multi-agent formation and particle swarm optimization (PSO) algorithm is employed to find the optimal solution. The developed framework is applied to the detailed design of a PC stair to demonstrate its practicability and efficiency.

查看原文本刊更多论文

利用多代理协调和粒子群优化技术实现预制混凝土构件中的智能多钢筋布局

对于预制混凝土（PC）构件而言，以产品为导向的设计对于实现工业化生产和精益施工起着至关重要的作用。由于不规则的混凝土轮廓和众多的预埋件，钢筋碰撞在 PC 组件中发生得更为频繁。本文提出了一种用于 PC 构件的自动详细设计框架，以生成无碰撞的多钢筋布局。受多代理群的编队移动能力启发，开发了多钢筋布局模块，以避免钢筋碰撞和间距不均。该模块包括三个子任务：虚拟领导者路径规划、碰撞代理避障和代理群编队优化。建立了调整多代理编队的优化模型，并采用粒子群优化（PSO）算法找到最优解。开发的框架被应用于 PC 楼梯的详细设计，以证明其实用性和效率。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Expert Systems with Applications 工程技术-工程：电子与电气

CiteScore

13.80

自引率

10.60%

发文量

2045

审稿时长

8.7 months

期刊介绍： Expert Systems With Applications is an international journal dedicated to the exchange of information on expert and intelligent systems used globally in industry, government, and universities. The journal emphasizes original papers covering the design, development, testing, implementation, and management of these systems, offering practical guidelines. It spans various sectors such as finance, engineering, marketing, law, project management, information management, medicine, and more. The journal also welcomes papers on multi-agent systems, knowledge management, neural networks, knowledge discovery, data mining, and other related areas, excluding applications to military/defense systems.