Optimization of the design process in construction projects by the implementation of the A360 collaboration tool

Arevalo, Jennifer; Palacios, Mauricio; Rodríguez, Simeón Collera; Farje, Julio

doi:10.1109/coniiti51147.2020.9240293

Cited by 1 publication

(2 citation statements)

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“…The A360 collaboration tool is a platform that delivers a centralized virtual area for storing BIM files, expressing them, & offering real-time comments from any device during the design process of BIM projects. The key point behind this research is to get a new solution to these problems identified by J. Arevalo et al [6]. The results of a BIM project demonstrated a decrease in waste, which reduced design time.…”

Section: A Existing Building Information Modeling Methodologymentioning

confidence: 96%

“…𝑃 𝑤𝑜𝑟𝑠𝑡,𝑐𝑙 = 𝑃 𝐿𝐵 + (𝑃 𝑈𝐵 − 𝑃 𝐿𝐵 + 1) * 𝑟𝑎𝑛𝑑𝑜𝑚 (6) The used parameters in the above equation ( 6) are defined in algorithm 2. Step When carefully considering how the AEHO parameters should configure, it could be possible to obtain a noticeable improvement in the algorithm's overall performance.…”

Section: ) Separation Operatormentioning

confidence: 99%

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AEHO: Apriori-Based Optimized Model for Building Construction to Time-Cost Tradeoff Modeling

Gupta

Trivedi

2022

IEEE Access

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The operations involved in building a structure interact and depend on one another. The model is developed using an Apriori-based swarm intelligence method, with the non-dominated solutions to the separation of elephant herding optimization technique as the swarm intelligence method. Also, population initialization, selection, and fitness evaluation for input parameters are used. This strategy optimizes construction time, cost, & environmental effects in an actual construction project. Compared to the original simulation-optimization integration, the suggested machine learning-based solution dramatically reduces computing time. A case study of a building construction project has been employed to show the usability of the proposed method. Similarly, the usefulness of the proposed AEHO model in optimal design is demonstrated by measuring many performance measures and a comparison with an already existing PSO optimization model. In addition, a coefficient value plot is established for visualizing the provided objectives, and an apriori method is presented for selecting one solution from the Pareto-optimal front that has been generated. This study intends to minimize time and cost for construction projects that include repetitive project activities by using the learning curve phenomenon, which reduces time and cost savings when considering the project's start and finish dates.

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Section: A Existing Building Information Modeling Methodologymentioning

confidence: 96%

Section: ) Separation Operatormentioning

confidence: 99%