Intelligent system in the cost control of commercial complex projects: Data-driven optimization method

Commercial complex development is featured by large scale, complex operational procedures, and prominent challenges in cost management. This study proposes a data-driven intelligent approach for optimizing cost management of commercial complex projects. First,it emphasizes the necessity of applying value engineering (VE) principles—specifically integrating the Function Analysis System Technique (FAST)—in cost control. Subsequently,a model framework is constructed and workflow procedures for construction cost management are formulated,with the core methodology being the integration of VE with a Fuzzy Analytic Hierarchy Process (FAHP) model. The pre-analysis phase involves defining VE study objectives via FAST,using FAHP to determine functional coefficients,and leveraging systematic cost analysis tools.By calculating cost and value coefficients, the model realizes real-time monitoring, thus avoiding irrational construction behaviors and supporting post-implementation reviews for continuous optimization. To validate the model’s effectiveness,an existing commercial complex project was selected for optimization. Comparative analysis shows that traditional methods resulted in a total cost of 74,886,333.3 yuan across civil engineering,building construction,HVAC,and electrical engineering,while the optimized approach reduced costs to 72,740,121.5 yuan,achieving a 2.87% cost reduction.

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Publication Details

Journal
PLoS ONE
Published
2026-06-18
DOI
https://doi.org/10.1371/journal.pone.0343158
Primary Topic
Value Engineering and Management
Type
article
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article

Intelligent system in the cost control of commercial complex projects: Data-driven optimization method

Y Li, Shiming Wang, Xiao Li, Debao Yao
PLoS ONE
Value Engineering and Management
article

Intelligent system in the cost control of commercial complex projects: Data-driven optimization method

Y Li, Shiming Wang, Xiao Li, Debao Yao
article en

Abstract

Commercial complex development is featured by large scale, complex operational procedures, and prominent challenges in cost management. This study proposes a data-driven intelligent approach for optimizing cost management of commercial complex projects. First,it emphasizes the necessity of applying value engineering (VE) principles—specifically integrating the Function Analysis System Technique (FAST)—in cost control. Subsequently,a model framework is constructed and workflow procedures for construction cost management are formulated,with the core methodology being the integration of VE with a Fuzzy Analytic Hierarchy Process (FAHP) model. The pre-analysis phase involves defining VE study objectives via FAST,using FAHP to determine functional coefficients,and leveraging systematic cost analysis tools.By calculating cost and value coefficients, the model realizes real-time monitoring, thus avoiding irrational construction behaviors and supporting post-implementation reviews for continuous optimization. To validate the model’s effectiveness,an existing commercial complex project was selected for optimization. Comparative analysis shows that traditional methods resulted in a total cost of 74,886,333.3 yuan across civil engineering,building construction,HVAC,and electrical engineering,while the optimized approach reduced costs to 72,740,121.5 yuan,achieving a 2.87% cost reduction.

PLoS ONEVol. 21(6)
Liaoning Technical University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 5%
Value Engineering and Management
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Intelligent system in the cost control of commercial complex projects: Data-driven optimization method — Y Li, Shiming Wang, et al. · PLoS ONE (2026) | TGRS Research Map | TGRS