Project Scheduling Research Articles

Cost Budget Analysis for Equal Distribution of Labour for Multi-Storey Buildings Construction

Although all resources on a construction project have their respective roles, the availability of labour significantly impacts how far the project moves forward and is completed. According to Kastor and Sirakoulis (2009), calculating the number of workers according to the construction schedule is crucial because, without this consideration, the resulting schedule may not be effective and efficient. process used for construction project resources to reduce fluctuations (Waluyo & Aditama, 2017). This research compares labour allocation, duration, and labour wage cost budgets under several conditions. These conditions include actual project conditions, planning, and results after levelling using an auto schedule. In project planning, the fluctuations obtained are pretty sharp. After the auto schedule levelling, the manpower no longer experienced overallocation, but fluctuations between weeks were still relatively high. This can happen because the quantity of work and labour in the construction projects under review is not comparable to the effects of project delays. The results obtained from the comparisons analyzed on the X-storey building construction project are that the auto schedule does not change the initial planning duration, which remains at 133 days. There was a disparity of 0.02% in auto schedule planning costs from 1,098,345,000.00. Meanwhile, in actual conditions, the labour cost budget increased by 0.12% from IDR 967,880,000.00 after the auto-schedule levelling process. It can be concluded that before resource levelling is carried out, it is necessary to review project scheduling and accelerate the duration of implementation, specifically if construction projects experience delays and other factors, so as not to cause fluctuations caused by the uneven quantity of work over some time.

Joint finance-based scheduling in construction: Internal interest rate approach

Joint finance-based scheduling in construction: Internal interest rate approach

Simulation-based hybrid genetic algorithms for the stochastic multi-mode resource-constrained project scheduling problem with minimized financial risk

Projects face uncertainties during implementation, and these uncertainties often lead to risk factors that disrupt successful project execution and cause a loss of profit. The stochastic project scheduling technique has been an effective avenue for reducing the risks in project management. Nevertheless, previous studies often neglected resource limits for minimizing the financial risks of projects in stochastic project scheduling problems. This study aims to optimize the conditional net present value at risk (CNPVaR), which measures a project’s expected loss of net present value (NPV) in a stochastic multi-mode resource-constrained project scheduling problem (SMRCPSP). Accordingly, considering the stochastic activity duration and cash flow, we construct a scenario-based optimization model for the SMRCPSP, where the solution (strategy) of the SMRCPSP is represented by a policy that includes an activity list and execution mode list; a scheduling policy is then employed to map the start times of activities at each decision time based on the solution. Three simulation-based hybrid genetic algorithms embedded with different iteration alternatives according to activity-based (AB) or resource-based (RB) scheduling policies are used. Furthermore, computational experiments are conducted to evaluate the proposed procedures through 480 instances. With respect to the CNPVaR, expected NPV, and algorithm stability metrics, the results of the experiments demonstrate that the genetic algorithm (GA) with local search based on the RB scheduling policy performed best compared with two other hybrids of the GA, the existing vibration damping optimization (VDO) method and a pure GA for large-sized projects. However, the VDO outperforms the other approaches according to the AB scheduling policy for small-scale projects. Additionally, a case study is conducted; the findings demonstrate that the risk attitude (confidence level) of project managers and the discount factor have impacts on the CNPVaR and expected NPV, but the CNPVaR is insensitive to the number of simulations.

Influence of BIM and Lean on Mitigating Delay Factors in Building Projects

Building projects are affected by various phenomena that can affect their success and continuity and, in the worst cases, can lead to project abandonment. The delay has been identified as one of the phenomena with the most significant impact and recurrence; therefore, mitigation actions are required. BIM and Lean Construction are two approaches with great potential to mitigate delay-generating factors. However, more studies need to be conducted to analyze their influence on mitigating schedule delays. Considering this gap, this paper focuses on analyzing the influence of Lean Construction tools, and BIM uses that favor mitigating the main factors that generate variations in the construction schedules of residential buildings. The research method was divided into five main stages: (1) Delay factors identification; (2) BIM uses identification; (3) Lean tools identification; (4) questionnaire design, validation, and application; and (5) influence quantitative analysis. A total of 20 delay factors, eight BIM uses, and eight Lean tools were selected. Next, a consultation was conducted with 50 building project managers and two residential building projects were analyzed. The findings show that implementing BIM and Lean tools greatly influences mitigating delay factors such as errors and deficiencies in design documents, inefficient project planning and scheduling, and poor communication and coordination with designers. BIM uses that have a strong influence on reducing delays include 4D construction planning and 4D construction analysis and optimization. In the Lean domain, the Last Planner System (LPS) and collaborative meetings have a high influence on mitigating delays. This study provides valuable insights for construction project managers to improve overall project efficiency by optimizing the implementation of BIM uses and Lean tools.

أثر استخدام تقنيات إدارة المشاريع على تطوير المشاريع بالتطبيق على شركات القطاع الخاص بالمنطقة الشرقية بالمملكة العربية السعودية

The aim of the research is to highlight the impact of the use of enterprise management techniques on enterprise development by applying to private sector companies in the eastern region of Saudi Arabia by clarifying the dimensions of enterprise development, as well as to reveal the impact of project management techniques on enterprise development in its dimensions (project scheduling, project resources, project cost, project risks, project quality). The researcher has relied on the analytical descriptive approach to achieve the objectives of the study. The identification was used as an information-gathering tool. This research was applied to a study community consisting of workers from private sector companies in the eastern region within Saudi Arabia. (SPSS). This research has yielded a series of important findings, the most significant of which is that there is a statistically significant effect between the techniques used in project management (as a separate variable) and enterprise development (as a follow-up variable) within private sector companies in the eastern region of Saudi Arabia. There is a statistically significant effect between the techniques used in project management (as a separate variable) and the scheduling of projects (as a first dimension of enterprise development) (as a follow-up variable) within private sector companies in the eastern region of Saudi Arabia. The researcher recommended the need for senior management to develop skills through continuous training in project management. There is a need for agreement between senior leadership in projects and departments on the determinants of strategic plan development. Resource management depends on the efficiency and effectiveness of project planning.

Assessing the implications of BIM on sustainability of construction projects through design risk management

PurposeDesign cost overrun is one of the prominent factor that can impact the sustainable delivery of the project. It can be encountered due to a lack of information flow, design variation, etc. thereby impacting the project budget, waste generation and schedule. An overarching impact of this is witnessed in the sustainability dimensions of the project, mainly in terms of economic and environmental aspects. This work, therefore, aims to assess the implications of a technological process, in the form of building information modelling (BIM), that can smoothen the design process and mitigate the risks, thus impacting the sustainability of the project holistically.Design/methodology/approachThe identified design risks in construction projects from the literature were initially analysed using a fuzzy inference system (FIS). This was followed by the focus group discussion with the project experts to understand the role of BIM in mitigating the project risks and, in turn, fulfilling the sustainability dimensions.FindingsThe FIS-based risk assessment found seven risks under the intolerable category for which the BIM functionalities associated with the common data environment (CDE), data storage and exchange and improved project visualization were studied as mitigation approaches. The obtained benefits were then subsequently corroborated with the achievement of three sustainability dimensions.Research limitations/implicationsThe conducted study strengthens the argument for the adoption of technological tools in the construction industry as they can serve multifaceted advantages. This has been shown through the use of BIM in risk mitigation, which inherently impacts project sustainability holistically.Originality/valueThe impact of BIM on all three dimensions of sustainability, i.e. social, economic and environmental, through its use in the mitigation of critical risks was one of the important findings. It presented a different picture as opposed to other studies that have mainly been dominated by the use of BIM to achieve environmental sustainability.

Quantitative Risk Analysis for Construction Projects Considering Risks Correlations and Fuzzy Logic

Construction projects have a high level of uncertainty because of several risk factors. Risks may affect projects in many ways resulting in time delays or cost overruns. Thus, the evaluation of uncertainty is required to get a reliable schedule. This research proposes a method for project scheduling considering risks. Expert judgment is used to identify and analyze risks. Potential risks are identified through Failure Mode Effect Analysis (FMEA). Risks impact is evaluated through fuzzy logic and Monte Carlo Simulation (MCS). The simulation considered the relationship between risks, and risks and activities.

Review of Research on Uncertain Repetitive Project Scheduling

With the continuous development of project management practice, the project often suffers from disturbance events in the actual execution activity, which leads to project delay and great economic losses.Uncertainty project scheduling studies have also received attention.Repetitive project is a type of project with its own characteristics in which the construction site can be divided into several independent units and all activities are repetitive on multiple units, such as high-rise buildings, highways, and pipeline works. The characteristics of repetitive project controlling paths and controlling activities have their own advantages in responding to uncertain events. This paper takes repetitive project scheduling as the object to sort out its uncertain scheduling research. Firstly, the uncertain research based on probability random theory, fuzzy set theory and robustness theory is summarized, and then the research on different scheduling strategies such as interruptions soft logic and multi-mode in repetitive project scheduling is further summarized. Finally, the current research status of uncertain reactive scheduling is summarized,and further research directions are pointed out.

Causes of Delay in EPC Projects: The Case of Indonesia

The construction industry is a significant part of the economy in developing countries. During Indonesia's 2010-2020 period, many large-scale EPC projects were launched to build new plants and infrastructure facilities. However, most of these projects experienced delays. This research aims to identify the causes of delays in EPC projects in Indonesia. It also investigates whether specific characteristics of EPC projects within the fertilizer industry in Indonesia, particularly those associated with state-owned companies, contribute to these delays. Data was collected through questionnaires with samples from company construction experts involved in EPC projects consisting of 41 owners, 14 contractors, and 12 consultants. The Relative Importance Index (RII) was subsequently computed, revealing the top ten delay causes for EPC projects in Indonesia based on the highest RII values consisting of delays in procuring equipment/materials, contractor difficulties in funding the project, ineffective project planning and scheduling, the winner of the tender is the lowest bidder, rework due to errors during construction, poor communication and coordination between parties involved in the project, delays in the work of design, disputes in understanding the EPC contract and project specification, unrealistic the duration of the project and delays in the owner's decision. Comparison of delay factors with other developing countries in Asia and Africa shows similarities. Notably, among these categories, contractor-related factors demonstrated the highest RII values. Spearman’s rank correlation coefficient shows that all respondents highly agreed with the individual ranking of delay factors.   

Maximizing Net Present Value for Resource Constraint Project Scheduling Problems with Payments at Event Occurrences Using Approximate Dynamic Programming

Resource Constraint Project Scheduling Problems with Discounted Cash Flows (RCPSPDC) focuses on maximizing the net present value by summing the discounted cash flows of project activities. An extension of this problem is the Payment at Event Occurrences (PEO) scheme, where the client makes multiple payments to the contractor upon completion of predefined activities, with additional final settlement at project completion. Numerous approximation methods such as metaheuristics have been proposed to solve this NP-hard problem. However, these methods suffer from parameter control and/or the computational cost of correcting infeasible solutions. Alternatively, approximate dynamic programming (ADP) sequentially generates a schedule based on strategies computed via Monte Carlo (MC) simulations. This saves the computations required for solution corrections, but its performance is highly dependent on its strategy. In this study, we propose the hybridization of ADP with three different metaheuristics to take advantage of their combined strengths, resulting in six different models. The Estimation of Distribution Algorithm (EDA) and Ant Colony Optimization (ACO) were used to recommend policies for ADP. A Discrete cCuckoo Search (DCS) further improved the schedules generated by ADP. Our experimental analysis performed on the j30, j60, and j90 datasets of PSPLIB has shown that ADP–DCS is better than ADP alone. Implementing the EDA and ACO as prioritization strategies for Monte Carlo simulations greatly improved the solutions with high statistical significance. In addition, models with the EDA showed better performance than those with ACO and random priority, especially when the number of events increased.

Navigating Gender Nuances: Assessing the Impact of AI on Employee Engagement in Slovenian Entrepreneurship

Background: Our research delved into exploring various selected facets of AI-driven employee engagement, from the gender perspective, among Slovenian entrepreneurs. Methods: This research is based on a random sample of 326 large enterprises and SMEs in Slovenia, with an entrepreneur completing a questionnaire in each enterprise. Results: Findings suggest that there are no significant differences between male and female entrepreneurs in Slovenia regarding various aspects of AI-supported entrepreneurial management practice including the following: AI-supported entrepreneurial culture, AI-enhanced leadership, adopting AI to reduce employee workload, and incorporating AI tools into work processes. The widespread integration of AI into entrepreneurship marks a transition to a business landscape that values inclusivity and equity, measuring success through creativity, strategic technology deployment, and leadership qualities, rather than relying on gender-based advantages or limitations. Our research also focused on the identification of gender differences in path coefficients regarding the impact of the four previously mentioned aspects of AI on employee engagement. While both genders see the value in using AI to alleviate employee workload, the path coefficients indicate that female entrepreneurs report higher effectiveness in this area, suggesting differences in the implementation of AI-integrated strategies or tool selection. Male entrepreneurs, on the other hand, appear to integrate AI tools into their work processes more extensively, particularly in areas requiring predictive analytics and project scheduling. This suggests a more technical application of AI in their enterprises. Conclusions: These findings contribute to understanding gender-specific approaches to AI in enterprises and their subsequent effects on employee engagement.

{MFPP(R). An R package for matrix-based flexible project planning

Project planning and scheduling are essential parts of project management. While project planning and scheduling tools are already available to support traditional project management approaches, flexible project management, such as agile, extreme and hybrid project planning, are only somewhat supported by computer algorithms. To the best of our knowledge, no existing R package for project planning and scheduling can support project planning and scheduling for flexible projects. In this paper, the goal is to fill this gap; to this end, the R package mfpp for matrix-based flexible project planning/scheduling is introduced and described. This package includes a comprehensive set of tools for project managers to schedule both traditional and flexible project plans. The use of the package is illustrated through examples.

Research and design of urban flood control and drainage dispatching system

In order to solve the problem of frequent flood disasters in urban areas, water conservancy models such as hydrological forecast, flood simulation and operation decision-making were studied and constructed for the waterway-region-urban flood control and drainage engineering facilities, and urban flood control and drainage operation system was designed with the model as the core. The overall structure of the system is "five horizontal and two vertical". The "five horizontal" bottom up are respectively the intelligent perception layer, cloud infrastructure layer, data layer, service layer and application layer, and the "two vertical" are respectively the security system and the standard specification system. On this basis, the function customization of the system is completed to achieve comprehensive display, early warning and forecast, flood simulation, risk assessment, project scheduling and intelligent decision-making functions.

Scheduling Analysis on the Heavy Rehabilitation Construction Project of the Dr. R. Koesma Tuban Hospital Building Using the PERT Method

Project scheduling is a key factor in achieving successful implementation as planned. Constraints such as limited resources, improper reporting, and high costs often become challenges in project management. Delays in project completion are very detrimental both in terms of cost and time. Just like what happened in the Rehabilitation and Heavy Construction Project of the Outpatient and Administration Building at Dr. R. Koesma Regional General Hospital in Tuban Regency, there was a delay of 10 days in its implementation. This research aims to determine the duration of the rehabilitation of the dr. R. Koesma Hospital building in Tuban Regency using the PERT method to improve time efficiency, reduce the risk of delays, and ensure overall project success. The research method used is combining two approaches, PERT method (Program Evaluation and Review Technique) to calculate the expected duration estimation of each work, and Microsoft Project 2016 to compile a project schedule that allows identification of critical activities and work network analysis. The results of the analysis using PERT method and Microsoft Project 2016 showed that the project was estimated to be completed in 115 days, faster than the planned 133 days. The probability that the project will be completed within the planned target duration T(d) = 133 days is 99.9%. Hence, there is a high probability that the project will be completed on time.

Evaluating the Delivery and Oversight of State-Funded Local Bridge Projects

State-funded local bridge projects face several challenges including but not limited to constrained budgets, increasing burden from state departments of transportation (DOT) staff, and the lack of expertise of some local personnel. By streamlining the delivery and oversight of state-funded projects through delegation, a collaborative and proactive approach can be achieved, ensuring the successful maintenance and development of local low-risk bridges, which are not on the National Highway System and have minimal to no environmental, right of way, utility, or railroad impacts. This paper offers a practical approach to evaluating programs focused on progressing project delivery by delegating specific tasks and responsibilities to local governments. Taken as a study case, Wisconsin Department of Transportation’s low-risk bridge pilot program was evaluated using both a quantitative methodology: data analysis using a data-driven statistical approach involving analysis of pilot and control group data, and an evaluation of the performance metrics developed by the state DOT; and a qualitative approach: a survey of local sponsors and stakeholders about the pilot project. The survey corroborated the findings derived from the data analysis: improved performance in project cost and schedule for pilot projects, highlighting consistency and reliability in the evaluation process. The integration of both methodologies resulted in valuable insights and experiences, providing valuable guidance to other states conducting similar program evaluations.

Artificial Intelligence in Project Management: Enhancing Efficiency and Decision-Making

This thesis explores the integration of Artificial Intelligence (AI) in project management practices to improve efficiency and decision-making processes. As organizations increasingly rely on project management methodologies to execute tasks, deliverables, and achieve objectives, the role of AI in enhancing these processes becomes pivotal. Through an examination of existing literature, case studies, and theoretical frameworks, this thesis investigates the potential benefits, challenges, and implications of incorporating AI technologies in project management. It aims to provide insights into how AI can optimize project planning, scheduling, resource allocation, risk management, and stakeholder communication. Additionally, the thesis explores the ethical considerations and societal impacts associated with the adoption of AI in project management. By analyzing real-world applications and theoretical perspectives, this research contributes to the understanding of how AI can be effectively utilized to streamline project management practices and drive organizational success in diverse industries.

The Continuous Time-Resource Trade-off Scheduling Problem with Time Windows

We introduce a variant of the cumulative scheduling problem (CuSP) characterized by continuous modes, time windows, and a criterion that involves safety margin maximization. The study of this variant is motivated by the Geospatial based Environment for Optimisation Systems Addressing Fire Emergencies Horizon 2020 Project, which is devoted to the design of evacuation plans in the face of natural disasters and more specifically, wildfire. People and goods have to be transferred from endangered places to safe places, and evacuation planning consists of scheduling evacuee moves along precomputed paths under arc capacities and deadlines. The resulting model is relevant in other contexts, such as project or industrial process scheduling. We consider here several formulations of the continuous time-resource trade-off scheduling problem (CTRTP-TW) with a safety maximization objective. We establish a complete complexity characterization distinguishing polynomial and NP-hard special cases depending on key parameters. We show that the problem with fixed sequencing (i.e., with predetermined overlap or precedence relations between activities) is convex. We then show that the preemptive variant is polynomial, and we propose lower and upper bounds based on this relaxation. A flow-based mixed-integer linear programming formulation is presented, from which a branch-and-cut exact method and an insertion heuristic are derived. An exact dedicated branch-and-bound algorithm is also designed. Extensive computational experiments are carried out to compare the different approaches on evacuation planning instances and on general CTRTP-TW instances. The experiments also show the interest of the continuous model compared with a previously proposed discrete approximation. History: Accepted by Andrea Lodi, Area Editor for Design & Analysis of Algorithms—Discrete. Funding: This work was funded by the Horizon 2020 Marie Skłodowska-Curie Research and Innovation Staff Exchange European Project 691161 GEO-SAFE (Geospatial based Environment for Optimisation Systems Addressing Fire Emergencie). This work has also been supported by ANITI, the Artificial and Natural Intelligence Toulouse Institute. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.0142 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2022.0142 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

A System Dynamics Approach to Feedback Processes in Project Scheduling

Projects, as catalysts for proactive transformation, offer a temporary and adaptable framework that effectively handles complexities (or uncertainties) within a competitive corporate landscape. Hence, the use of an effective project management framework, such as Dynamic Project Scheduling (DPS), is a method to handle intricacies in order to accomplish organizational objectives. DPS refers to a triangle interaction involving baseline scheduling, schedule risk analysis, and project control while supporting schedule adjustment in response to changes and uncertainties. However, there is a lack of information regarding studies that have investigated the feedback mechanisms among DPS components. This study was designed to examine the counterintuitive relationships between these components using system dynamics. The quantities within the DPS system were identified and defined. A casual loop diagram was used to illustrate the interactions among these quantities. Subsequently, a Stock and Flow Diagram (SFD) was created to identify the inputs, states, and flow mechanisms within the DPS. Using the SFD, a system dynamics expression was generated which was then employed to compute the rate of change of the Budgeted Cost of Work Remaining (BCWR) for two projects at different time intervals. The results properly indicated the period of idleness during project execution. The use of BCWR rather than schedule variance provides a more effective visual representation for evaluating performance and tracking progress. The BCWR and planned value exhibit contrasting trends, highlighting the importance of earned value quantities in project control. The use of system dynamics in project management can enhance the planning and scheduling phase, allow project managers to monitor pertinent performance measures, and optimize project outcomes through informed decisions.

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.

Emerge of scaling in project schedules

Emerge of scaling in project schedules