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利用混合多宇宙优化器模型解决大规模离散时间-成本权衡问题。

Solving large-scale discrete time-cost trade-off problem using hybrid multi-verse optimizer model.

机构信息

Department of Construction Engineering and Management, Ho Chi Minh City University of Technology (HCMUT), Vietnam National University (VNU-HCM), Ho Chi Minh City, Vietnam.

出版信息

Sci Rep. 2023 Feb 3;13(1):1987. doi: 10.1038/s41598-023-29050-9.

Abstract

The analysis of the relationship between time and cost is a crucial aspect of construction project management. Various optimization techniques have been developed to solve time-cost trade-off problems. A hybrid multi-verse optimizer model (hDMVO) is introduced in this study, which combines the multi-verse optimizer (MVO) and the sine cosine algorithm (SCA) to address the discrete time-cost trade-off problem (DTCTP). The algorithm's optimality is evaluated by using 23 well-known benchmark test functions. The results demonstrate that hDMVO is competitive with MVO, SCA, the dragonfly algorithm and ant lion optimization. The performance of hDMVO is evaluated using four benchmark test problems of DTCTP, including two medium-scale instances (63 activities) and two large-scale instances (630 activities). The results indicate that hDMVO can provide superior solutions in the time-cost optimization of large-scale and complex projects compared to previous algorithms.

摘要

时间-成本分析是建设工程项目管理的一个关键方面。已经开发了各种优化技术来解决时间-成本权衡问题。本研究引入了一种混合多宇宙优化器模型(hDMVO),它将多宇宙优化器(MVO)和正弦余弦算法(SCA)结合起来解决离散时间-成本权衡问题(DTCTP)。该算法的最优性通过使用 23 个著名的基准测试函数进行评估。结果表明,hDMVO 与 MVO、SCA、蜻蜓算法和蚁狮优化算法具有竞争力。通过四个 DTCTP 的基准测试问题评估 hDMVO 的性能,包括两个中等规模的实例(63 个活动)和两个大规模的实例(630 个活动)。结果表明,与以前的算法相比,hDMVO 可以在大规模和复杂项目的时间-成本优化中提供更好的解决方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9e53/9898292/6dd211f45949/41598_2023_29050_Fig1_HTML.jpg

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