一个改进的多目标动画麦优化算法,用于资源受限的建筑项目组织设计
Qing Xue1, Chunjiang Wu2, Jiyang Nie1
1School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, China.
Scientific reports
|February 23, 2026
概括
本研究介绍了多目标动画麦优化 (MOAOO) 算法,以改进建筑项目组织设计. MOAOO提高了资源配置,平衡了成本和持续时间等相互矛盾的目标,并证明了工程管理的实际价值.
科学领域:
- 工程管理工程管理工程管理
- 计算智能是一种计算智能.
- 优化算法 优化算法
背景情况:
- 全球城市化推动了大规模的建筑项目,需要优化组织设计.
- 传统方法在资源效率,多目标冲突解决和动态调整方面面临挑战.
- 现有的优化技术对于复杂的建筑项目组织设计是不够的.
研究的目的:
- 开发动画麦优化算法 (MOAOO) 的第一个多目标扩展,用于建筑项目组织设计.
- 解决资源分配和多目标冲突管理中的经验决策的局限性.
- 为增强动态调整能力引入一种新的优化方法.
主要方法:
- 通过扩展动画麦优化生物机制来开发MOAOO.
- 整合了混合位置更新规则,使用精英参考点和随机扰动.
- 实施了三层约束处理机制和双值趋同监控系统.
- 集成的动态精英保留,非主导排序和动态档案机制,用于协作优化.
主要成果:
- 在 ZDT 测试函数上,MOAOO 证明了与先进算法 (Pre-DEMO,MOEA/D-OED,Pi-MOEA) 相比具有竞争力的性能.
- 在一个案例研究中,实现了资源波动 (72.7%) 的显著减少.
- 成功地平衡了相互矛盾的目标:持续时间 (279天) 和成本 (1.34万美元).
- 在平均118次代中有效地融合.
结论:
- MOAOO是AOO的首个多目标变体,为建筑项目设计提供有效的协作优化.
- 该算法克服了传统方法的局限性,在施工调度中提供了实际价值.
- MOAOO为复杂,多目标的工程管理挑战提供了强大而高效的解决方案.
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