Scheduling Of Construction Projects Research Articles

Intelligent scheduling optimization of prefabricated components for assembly buildings

Prefabricated construction, as an emerging architectural model, has the characteristics of fast construction process and flexible design, and has been widely used in the field of architecture in China. As the core component of prefabricated buildings, the schedule of prefabricated components directly affects the progress and quality of the project. This study extends the volume of prefabricated components from a single building to a group of buildings, designs and solves an intelligent scheduling scheme model based on project construction schedule and procurement plan, and proposes two reference building group scheduling schemes and their applicable conditions. Genetic algorithm is used to optimize vehicle scheduling and transportation paths to achieve intelligent scheduling of prefabricated components in prefabricated building groups, ensuring project progress and quality.

Fuzzy-Graphical Evaluation and Review Technique for Scheduling Construction Projects

Fuzzy-Graphical Evaluation and Review Technique for Scheduling Construction Projects

Building Information Modeling (BIM) for Construction Project Schedule Management: A Review

Nowadays, the implementation and application of the BIM process in construction project management is a pressing need. This aligns with the global development trends in the construction sector and project information management in general. Numerous scholars and companies are actively engaged in learning, understanding, and investigating various aspects of BIM to stay up-to-date and meet the inevitable developmental requirements. This study focuses on the role and application of BIM, intending to identify limitations that hinder its fulfillment of expectations in project schedule management. In addition, it explores studies that show how other countries have effectively employed BIM in project management and progress tracking throughout the project lifecycle. The study aims to address three main objectives: (a) comprehensively examine and provide evidence related to the concept of BIM in project schedule management, (b) present the benefits of applying BIM in comparison to traditional methods in project management and operation, and (c) identify limitations stemming from various factors that may pose challenges in the application of BIM in project schedule management.

Accelerating the middle – rise building construction duration using BIM 4D, a case study in central Jakarta

Construction planning involves scheduling and sequencing of project activities for proper execution. Research was conducted to obtain and enhance construction project scheduling, which was good and in accordance with the targets achieved. The results of the project performance analysis in the 9th month using the Earned Value Method resulted in SPI <1 and SV <0, indicating that the project experienced delays. Scheduling using the PDM based on the actual duration of the project shows that the project will be completed in 511 days. The project duration can be accelerated to 429 days by combining overlap and overtime methods. The scheduling results were simulated using BIM 4D to generate a visualization of the scheduling to improve the project monitoring process.

A study on time schedules for construction projects in Hanoi, Vietnam

With its position as the capital, Hanoi is the political center as well as the second largest economic center of the country. Therefore, the city is always allocated a large budget in construction investment to create material facilities for political tasks and economic and social development. During the implementation of construction projects, a number of difficulties and limitations have appeared. In which, projects are delayed in construction and disbursement, reducing investment efficiency and not meeting the expectations of the government and people. From this fact, the authors have conducted a study to evaluate the causes affecting the time schedule of construction projects in Hanoi. The method F-APH (Fuzzy Analytic Hierarchy Process) was used to analyze data objectively and accurately about the causes affecting the time schedule. From there, these causes are classified into groups of subjective causes (from within the project) and groups of objective causes (from outside the project). The results show that subjective causes, originating from project participants, have a stronger influence than objective causes. A number of specific proposals to the actors involved in construction projects are made to eliminate or limit the impact of the causes of construction progress.

Generation of Construction Scheduling through Machine Learning and BIM: A Blueprint

Recent advancements in machine learning (ML) applications have set the stage for the development of autonomous construction project scheduling systems. This study presents a blueprint to demonstrate how construction project schedules can be generated automatically by employing machine learning (ML) and building information modeling (BIM). The proposed solution should utilize building information modeling (BIM) international foundation class (IFC) 3D files of previous projects to train the ML model. The training schedules (the dependent variable) are intended to be prepared by an experienced scheduler, and the 3D BIM files should be used as the source of the scheduled activities. Using the ML model can enhance the generalization of model application to different construction projects. Furthermore, the cost and required resources for each activity could be generated. Accordingly, unlike other solutions, the proposed solution could sequence activities based on an ML model instead of manually developed constraint matrices. The proposed solution is intended to generate the duration, cost, and required resources for each activity.

Exploring Cost Variability and Risk Management Optimization in Natural Disaster Prevention Projects

The purpose of this study is to analyze the causes of cost variation in natural disaster prevention projects (NDPPs) in Gyeongsangbuk-do, South Korea, and develop tailored cost and risk management strategies. Utilizing a binary logistic regression model, this research uniquely focuses on the Gyeongsangbuk-do region, gathering data from 244 stakeholders through an online survey. The study identifies critical variables influencing cost deviation, including project management risk (PMR), project costing and execution risk (PCER), project execution strategy risk (PESR), construction project risk (CPR), project cost and schedule risk (PCSR), project management challenges (PMCs), and construction project subcontractor and safety management (CPSSM). Significant findings revealed PMR (OR = 3.744, 95% C.I. [1.657, 8.457]), PCER (OR = 5.068, 95% C.I. [2.236, 11.484]), and PESR (OR = 3.447, 95% C.I. [1.853, 6.413]) as the primary causes of cost deviation, alongside the notable impacts of other factors such as CPSSM. The developed predictive model is instrumental for NDPP stakeholders in Gyeongsangbuk-do, providing advanced risk management capabilities and aiding in effective preventive measures. This study not only corroborates theoretical hypotheses from previous research but also offers new insights into cost deviation causes in NDPPs, thereby enhancing strategic decision-making and advancing risk management perspectives.

Analisa Produktivitas Tenaga Kerja Pada Proyek Pembangunan Gedung Bertingkat Dengan Menggunakan Metode Time Study (Studi Kasus: Proyek Pembangunan Gedung Kejaksaan Tinggi Kalimantan Tengah)

The productivity of workers determines the success of the implementation of the construction project schedule, because it has an impact on the compatibility between the planning of the construction schedule and the progress of work in the field. The worker productivity that will be calculated is the work of reinforcing beams in the Central Kalimantan High Prosecutor's Office building construction project. The calculation of worker productivity will be carried out using the time study method.This study aims to determine the extent of worker productivity during working hours in the morning and evening. The method used in this research is the time study method, which is the measurement of labor productivity in the field by determining the standard time of a job. From this method can be seen the comparison of worker productivity from the results of a job. In this case study, the factors that affect worker productivity will be identified. The data collection technique in this study used a questionnaire by giving written questions to respondents that were relevant to the research objectives. Based on the results of the analysis, it is known that the productivity of workers in the morning higher with an average weight of 41,825 kg/hour than in the afternoon of 40,433 kg/hour. Where on the first day the productivity of morning workers is 12,56% and in the afternoon it is 11,97%. On the second day the productivity of morning workers is 12,81% and in the afternoon it is 12,18%. On the third day the productivity of morning workers is 12,68% and in the afternoon 12,43%. On the fourth day the productivity of morning workers is 12,85% and in the afternoon 12,52%. In general, it can be seen that the productivity of workers in the morning is higher than that of workers in the afternoon. There are 3 categories of factors that influence worker productivity: not influential (TB) are wind gusts; influential (B) are weather factors; number of workers, age, wages; managerial factors; effectiveness of working hours; and very influential are skill factors

Integration of resource supply management and scheduling of construction projects using multi-objective whale optimization algorithm and NSGA-II

Integration of resource supply management and scheduling of construction projects using multi-objective whale optimization algorithm and NSGA-II

Developing a Bayesian belief network model for quantifying and predicting claim causes-related schedule delays

Nowadays, construction claims have become an inevitable part of the construction project, and they have a serious impact on the project schedule. This study aims to develop a Bayesian belief network (BBN) model for quantifying and predicting claim cause-related schedule delays in Vietnam. Based on data from survey questionnaires and interviews with experts, 23 critical claim causes of construction project schedule delays and 17 significant cause-effect relationship pairs were found and used to build the BBNs models. The results obtained from the BBNs models are good at quantifying the probability of schedule delays in three different case study projects. In the case study of a transportation project, for example, there is a major delay of 34 months, which is about 38.64% of the original length of the project. The model predicted that there is a 69% chance that the project’s schedule delay will be more than 20% of the original length. Using these BBNs models, industry practitioners can prevent claim causes-related schedule delays early. This approach is general and can be applied to any construction project in other countries with small adjustments, especially in the case of developing countries similar to Vietnam.

Analysis of factors influencing resource scheduling for emergency construction projects considering multiple spatial characteristics

In response to the growing frequency of international emergencies, the demand for resources dedicated to emergency construction projects has significantly increased due to their pivotal role in disaster containment and mitigation. This article examines the factors influencing the allocation of multi-spatial resources for such projects, conducting both causal and hierarchical analyses to unveil their interdependent mechanisms. It addresses a theoretical research gap in resource scheduling through bibliometric analysis. The study utilizes the Fuzzy Decision-Making Laboratory Analysis (Fuzzy-DEMATEL) method to identify key factors within the system and constructs a hierarchical model using Interpretive Structural Modeling (ISM) to systematically analyze the factors affecting multi-space resource allocation in emergency construction projects. The results reveal 43 influencing factors, categorized into 11 levels, with the political and social environment, resource scheduling determination, and design changes standing out as the primary influencers. Additionally, the article proposes a three-tiered strategy based on experimental results to offer theoretical insights for multi-spatial resource scheduling in emergency construction projects.

Optimized variable resource allocation framework for scheduling of fast-track industrial construction projects

Efficient scheduling and resource allocation for large-scale industrial projects is challenging due to their size and complexity, especially with fast-track contracts, which often lack detailed information during the early planning phase. This paper introduces a data-driven workface planning framework to enhance scheduling and resource allocation while accommodating uncertainties and constraints (e.g., minimum and maximum resource allocation curves, dynamic predecessor relationships, congestion limits). This framework employs an integrated approach, combining time-stepped simulation with graph-based optimization. By leveraging historical data and expert knowledge, the data-driven framework mitigates certain subjective assumptions, including durations and resource allocations. In practical application, the framework generates near-optimal schedules, even with limited information. Applying the framework to a fast-track industrial construction project case study demonstrated enhanced resource allocation. These findings offer practical benefits to industrial projects regarding time and cost savings and serve as a foundation for future research in data-driven project planning approaches.

Bi-objective Optimization for Resource-constrained Robust Construction Project Scheduling

Bi-objective Optimization for Resource-constrained Robust Construction Project Scheduling

Transformer language model for mapping construction schedule activities to uniformat categories

Creating consistency among project schedule data, BIM, and payment applications requires activities in a construction schedule to be mapped with the most relevant ASTM Uniformat classifications. To do so, we introduce UniformatBridge, a new transformer-based natural language processing model, that automatically labels activities in a project schedule with Uniformat classification. Our model introduces construction sequencing tokens that capture logistically-constrained predecessor and successor activities into BERT architecture. We also introduce a dataset of real-world construction project schedules with their ground-truth Uniformat classifications for validation. Experimental results using this dataset achieve F1-scores of 0.93 and 0.87 when matching unstructured schedule data to Uniformat Level 2 and 3 classifications, respectively. We share how our method unlocks development of new techniques to (1) automatically create 4D BIM, and (2) computer-vision progress monitoring to tie semantic segmentation of reality capture data based on Uniformat classes against schedule or payment application data structures, with/without BIM.

A Guideline of Earned Value Method (EVM) Implementation as Decision Baseline on Acceleration Solutions for Construction Project Scheduling

Implementing an efficient performance monitoring system is necessary to complete a facility building project on time, on budget, and by established standards and specifications. Inappropriate system monitoring process could lead to project failures such as delay which commonly occurs. If the delay happens, it is necessary to accelerate work productivity to overcome it. Earned value method (EVM) is one of the suggested global standards for measuring project performance. It effectively combines scope, cost, and schedule metrics and can provide a clear picture of the state of the project as of the control date. It also predicts the time prolong and completion budget. This paper proposes a guideline to implement EVM as a decision baseline on acceleration solutions for construction project scheduling by conducting an article review, since the EVM can predict the project’s time estimates at completion (TE). According to the guideline, when arranging network planning based on construction actual work performed, it is essential to use TE as the completion time. From the critical activities in network planning, contractors can conduct the acceleration process such as additional work hours (overtime) and additional manpower. This acceleration scenario later could be implemented in the project as the solution to overcome the delay.

BIM-INTEGRATED SYSTEM: A SUCCESSFUL ALTERNATIVE FOR ESTIMATING CASH FLOW IN BUILDING PROJECTS

Cash flow calculation is an essential economic aspect of evaluating the success of a construction project. Strong cash flow positively impacts not only project effectiveness but also company profitability. Cash flow calculation is a good way for the contractors to avoid risks related to delay, cost overrun, or incompletion caused by financial deficits in the project’s performance. Building Information Modeling (BIM) is a revolutionary technology 4.0 that has been mandated and adopted by many countries all over the world. In Vietnam, a roadmap for BIM application in the construction sector was issued in 2023, under which obligatory new investment projects in public investment state capital provide BIM files to serve the appraisal of feasibility study reports, construction designs carried out after fundamental designs, applications for construction permits, and acceptance testing tasks. However, BIM authoring programming is still limited to cost management, especially cash flow calculations, because Vietnamese contractors are still facing a lot of difficulties in applying BIM to their projects, especially cash flow calculations. Therefore, this paper proposes a BIM-integrated system for calculating construction cash flow at the early phase of the project life cycle. The proposed system includes four modules: BIM visualization and data integration, construction cost estimating, construction project scheduling, and project cash flow calculation. The main functionality of the BIM visualization and data integration module is to provide a 3D visualized model with enough geometric and non-geometric data for the project quantity take-off. The functionality of the construction cost estimating module is to provide the direct cost categories, such as labor, material, and machine, and the indirect cost categories to perform all work tasks in the construction project. The main functionality of the construction project scheduling module is to provide the required time to complete all work tasks in the project implementation process. The main functionality of the project cash flow calculating module is to present cash inflows such as advance payment, payments from the owner, and cash outflows such as construction costs, equipment costs, project management costs, and project consultant costs to carry out the projects. The BIM-integrated system will make the calculation process of construction project cash flow easier and more accurate.

A heuristic rule adaptive selection approach for multi-work package project scheduling problem

Effectively scheduling a project is crucial for its success, especially after generating work packages from the work breakdown structure during the planning phase. Nevertheless, solving project scheduling problems with multiple work packages is challenging due to the inefficient utilization of work package information in existing scheduling approaches. To address this issue, this paper proposes the Heuristic Rule Adaptive Selection (HAS) approach for the Multi-Work Package Project Scheduling Problem (MWPSP). This approach involves work package information and employs reinforcement learning (RL) for intelligent decision-making in scheduling. First, the MWPSP with the optimization objective of minimizing the Portfolio Delay (PDEL) and the Average Percent Delay (APD) is defined, and a scheduling environment is established that integrates information from both work packages and tasks. Second, a Double Deep Q-network (DDQN) is employed to train agents for adaptively selecting heuristic rules of tasks and work packages. The performance of the HAS approach is then evaluated using a case project and the newly created MWPSP dataset. The experimental results demonstrate that the HAS approach exhibits superior solution quality and computational efficiency in optimizing PDEL and APD compared to heuristics approaches, e.g., single-priority rule-based heuristics and genetic algorithms. This achievement sets the stage for the development of next-generation adaptive scheduling for construction projects.

Analyzing the factors affecting construction project schedules amidst COVID-19 pandemic

The global health crisis caused by the COVID-19 pandemic led to disruptions and challenges across many business sectors, including the construction industry. A serious ramification of the pandemic on the construction industry was an increase in the number of project schedule delays that affected a multitude of projects around the world. Although the current literature explores the factors that cause project schedule delays, little research is available on the impact of variables, such as the size of the industry, type of project, and category of the organization, on the delays. This study used a four-step approach to address this knowledge gap by performing a comprehensive literature search, developing a survey, distributing the survey online, and conducting a quantitative analysis of the responses. The study's findings revealed that the factors contributing to project schedule overruns during the pandemic were diverse and differed with the variables cited above. Distinct differences were observed in areas such as procurement of materials and changes in material specifications and prices. This research sheds light on the multifaceted nature of the variables that impacted construction project schedules during the COVID-19 pandemic and provides valuable insights for industry stakeholders as they seek to establish effective strategies that will minimize risks and enhance project delivery during future periods of crisis.

A quantified risk-based approach to construction noise and vibration management

The management of environmental noise and vibration impacts from construction activities can significantly influence the scheduling, program, activities, and costs of construction projects. While there are a number of mitigation and management measures available to the construction site to control their environmental impacts upon neighboring sensitive receivers, efforts to reduce impacts should be focused on taking the steps that will result in the greatest reduction to the overall project’s environmental risk profile. In order to identify the countermeasures with the highest efficacy to reduce the overall risk, it is advantageous to quantify noise and vibration impacts based on ordinal metrics such as decibels and degree of annoyance. This paper describes a proposed method to quantify construction noise and vibration risk in order to improve the identification and selection of the countermeasures that should be implemented on site.

Optimization-based Scheduling of Construction Projects with Generalized Precedence Relationships: A Real-Life Case Study

Optimization-based Scheduling of Construction Projects with Generalized Precedence Relationships: A Real-Life Case Study