相关实验视频
Updated: Sep 18, 2025

Operation of the Collaborative Composite Manufacturing CCM System
Published on: October 1, 2019
集成决策支持系统,用于优化线性重复建筑项目的时间和成本权衡
Ahmed Gouda Mohamed1, Ali Hassan Ali2,3, Ahmed Adel Abdelhady2
1Construction Engineering and Management Department, Civil Engineering, Faculty of Engineering, The British University in Egypt (BUE), El Sherouk City, 11837, Cairo, Egypt. ahmed.ghanem@bue.edu.eg.
本研究介绍了一种用于优化重复性建筑项目的元启发性框架,比较基因算法 (GA) 和粒子群优化 (PSO) 的时间-成本权衡. 这两种算法都提高了效率,PSO在降低成本和减少持续时间方面略有优势.
科学领域:
- 建设管理建设管理.
- 运营研究 运营研究
- 计算智能是一种计算智能.
背景情况:
- 线性重复建筑项目面临着复杂的时间和成本优化挑战.
- 传统的调度方法往往不足以应对这些复杂性.
- 超启发式方法为增强项目优化提供了潜力.
研究的目的:
- 为重复性建筑项目引入和评估基于元启发的时间-成本权衡 (TCT) 框架.
- 为了比较评估基因算法 (GA) 和粒子群优化 (PSO) 对线性重复项目时间-成本权衡 (LRPTCT) 问题的有效性.
- 在TCT框架内整合任务分解和平衡线 (LOB) 调度.
主要方法:
- 开发了一个TCT框架,利用GA和PSO来解决LRPTCT的问题.
- 采用了任务分解和平衡线 (LOB) 调度技术.
- 将编程约束集成到GA和PSO的适应性函数中以进行优化.
主要成果:
- 总的来说,GA降低了直接 (3.25%),间接 (20%) 和总 (7%) 的建筑成本.
- 公用事业单位实现了直接成本减少4%和总项目持续时间减少20%.
- 这两种算法都在资源利用和调度效率方面取得了显著的改进.
结论:
- 基于元启发的TCT框架有效地优化了线性重复项目的时间表.
- GA和PSO为应对LRPTCT挑战提供了可行的,比较的策略.
- 这项研究提供了一种可复制的方法来增强建筑项目管理和决策.
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