A review of construction management challenges and BIM-based solutions: perspectives from the schedule, cost, quality, and safety management

Parsamehr, Mohammadsaeid; Perera, Udara Sachinthana; Dodanwala, Tharindu C.; Perera, Piyaruwan; Ruparathna, Rajeev

doi:10.1007/s42107-022-00501-4

Cited by 53 publications

(23 citation statements)

References 240 publications

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“…This broader applicability enhances the significance and relevance of the findings in the context of various industries and settings. Parsamehr [ 49 ] proposed a method to improve the accuracy of building maintenance cost estimation, mitigate the risk of overestimating maintenance costs, and optimize maintenance resource allocation. While this method has demonstrated universality in certain application fields, its applicability to other related fields remains limited.…”

Section: Resultsmentioning

confidence: 99%

Optimizing green supply chain circular economy in smart cities with integrated machine learning technology

Liu,

Guan,

Wang

et al. 2024

Heliyon

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Section: Resultsmentioning

confidence: 99%

Optimizing green supply chain circular economy in smart cities with integrated machine learning technology

Liu,

Guan,

Wang

et al. 2024

Heliyon

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“…11 [25], [28], [31], [36], [44], [45], [48]- [51], [62], [71]- [74] 35 Increased Visualization Tool that conveys key information to stakeholders improving workflow. 2 [36], [40] 36…”

Section: Simulation Of Discrete Eventsmentioning

confidence: 99%

Implementation of the Lean Construction Methodology in the Management of the Material Transportation Process- A Review

Iparraguirre-Villanueva,

Taico-Valverde,

Velezmoro-Abanto

et al. 2023

IJETT

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One of the biggest problems in the construction industry that often generates delays and loss of value in the construction site are the processes related to the management of material transportation. These processes are decisive in collaborating in the search for greater productivity. Lean Construction (LC), together with its tools and techniques, is a methodology that is being implemented in the sector and whose objective is the identification and elimination of waste on-site. The objective of this work is to analyze the impact of implementing the LC methodology in the construction sector focused on the transportation of materials, as well as to verify the other benefits of the methodology. In this systematic literature review (SLR) work, seven online databases were used to search for scientific manuscripts related to the LC methodology and the materials transportation process; after being analyzed and systematized using the prism methodology and the inclusion and exclusion criteria, 54 manuscripts were selected, seeking to answer the research questions. The results indicate that 21 manuscripts state that the benefits provided by the application and execution of LC are fundamental to ensure the execution and success of the project. Also, LC tools and techniques are essential to improve productivity. Also, the analysis shows that the main challenges are lack of management commitment, lack of willingness to change the culture, lack of skills and lack of training. Finally, the importance of management in the building materials supply chain is demonstrated by identifying the drivers and enablers.

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“…Cheng et al proposed extensible scheduling related to communication scheduling in the context of resource constraint scenarios in an industrial IoT based on learning architecture to reduce the waste of communication resources and ensure real-time communication [18]. Parsamehr et al proposed a method to optimize scheduling using a building information model in the context of resource-constrained schedule, cost, and safety management in building construction, thus optimizing the scheduling of resources while effectively building a construction decision framework [19]. Tavakolan and Nikoukar proposed a hybrid meta-heuristic algorithm based on the analysis of project resources to solve the multi-objective optimization problem in construction project planning [20].…”

Section: Related Workmentioning

confidence: 99%

Application of Improved Artificial Immune System Algorithm Based on Applied Mathematics for Optimization of Manpower Allocation in Construction Engineering

Huang¹,

Bai

2023

Processes

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The outbreak of the COVID-19 pandemic has led construction companies to prioritize the intelligent and optimal scheduling of human resources in construction projects to reduce costs. This study addresses the problem of heterogeneity in human resource scheduling in construction projects, presents a mathematical model with generic human resources as an example, proposes an improved artificial immune system (NAIS) algorithm to solve the problem, and verifies its effectiveness. Experimental results show that the NAIS algorithm achieves the optimal duration of 9 days in just 2 s using the Matrix Laboratory (MATLAB), which is significantly faster than mathematical optimization technique software (CPLEX), thus confirming the feasibility of the NAIS algorithm. Additionally, the average PD values for the NAIS algorithm, calculated for different worker counts, skills, and the number of tasks, were lower compared to the comparison algorithm. Overall, the NAIS algorithm effectively addresses the heterogeneous problem of human resource scheduling in construction projects with multiple modes, thereby optimizing construction engineering labor allocation.

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A review of construction management challenges and BIM-based solutions: perspectives from the schedule, cost, quality, and safety management

Cited by 53 publications

References 240 publications

Optimizing green supply chain circular economy in smart cities with integrated machine learning technology

Optimizing green supply chain circular economy in smart cities with integrated machine learning technology

Implementation of the Lean Construction Methodology in the Management of the Material Transportation Process- A Review

Application of Improved Artificial Immune System Algorithm Based on Applied Mathematics for Optimization of Manpower Allocation in Construction Engineering

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