{"title":"Analysis of Multi-Objective Integrated Management System of Engineering Project Based on Ant Colony Algorithm","authors":"Ruifu Qi, Yongjun Qi, Hailing Tang","doi":"10.1109/ICDCECE57866.2023.10150990","DOIUrl":null,"url":null,"abstract":"In the field of engineering construction, project management is a very important topic because it can promote the efficient development of the project. In the process of project investment decision-making, the core is the construction and operation of the whole project. This paper can systematically improve the management of engineering projects through ant colony algorithm. This paper mainly uses the methods of experimental analysis and principal component analysis to deeply study the multi-objective integrated management system of engineering project based on ant colony algorithm. The experimental data shows that at the quality level, the results of the two main factors meet the basic requirements, reaching more than 85%. The system can effectively improve the management efficiency and level of engineering projects, optimize the scheduling scheme of engineering projects, and improve the execution efficiency and quality of engineering projects.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDCECE57866.2023.10150990","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In the field of engineering construction, project management is a very important topic because it can promote the efficient development of the project. In the process of project investment decision-making, the core is the construction and operation of the whole project. This paper can systematically improve the management of engineering projects through ant colony algorithm. This paper mainly uses the methods of experimental analysis and principal component analysis to deeply study the multi-objective integrated management system of engineering project based on ant colony algorithm. The experimental data shows that at the quality level, the results of the two main factors meet the basic requirements, reaching more than 85%. The system can effectively improve the management efficiency and level of engineering projects, optimize the scheduling scheme of engineering projects, and improve the execution efficiency and quality of engineering projects.