Repetitive Projects Research Articles

Multi-Objective Resource-Constrained Scheduling in Large and Repetitive Construction Projects

Effective resource management constitutes a cornerstone of construction project success. This is a challenging combinatorial optimization problem with multiple and contradictory objectives whose complexity rises disproportionally with the project size and special characteristics (e.g., repetitive projects). While relevant work exists, there is still a need for thorough modeling of the practical implications of non-optimal decisions. This study proposes a multi-objective model, which can realistically represent the actual loss from not meeting the resource utilization priorities and constraints of a given project, including parameters that assess the cost of exceeding the daily resource availability, the cost of moving resources in and out of the worksite, and the cost of delaying the project completion. Optimization is performed using Genetic Algorithms, with problem setups organized in a spreadsheet format for enhanced readability and the solving is conducted via commercial software. A case study consisting of 16 repetitive projects, totaling 160 activities, tested under different objective and constraint scenarios is used to evaluate the algorithm effectiveness in different project management priorities. The main study conclusions emphasize the importance of conducting multiple analyses for effective decision-making, the increasing necessity for formal optimization as a project’s size and complexity increase, and the significant support that formal optimization provides in customizing resource allocation decisions in construction projects.

Modeling and optimizing linear projects using LSM and Non-dominated Sorting Genetic Algorithm (NSGA-II)

Linear projects are a special type of repetitive projects. Major disadvantages have been shown when using the critical path method (CPM) for linear project problems. So, to overcome these shortcomings linear scheduling method (LSM) was used to analyze linear projects. There are different types of activities in linear projects. However, existing mathematical models for LSM cannot represent all types of linear project activities. Therefore, this paper presents a mathematical model that can represent all types of activities using matrices. Moreover, the mathematical model is then used to create an optimization model that minimizes the project duration and cost using non-dominated sorting genetic algorithm II (NSGA-II). The two models can help project managers in scheduling real-life linear projects and find optimum linear project schedules. This paper introduces an optimization model for linear projects that utilizes matrices, offering a different approach in the field of linear project optimization.

Scheduling of Repetitive Projects with Multiple Objectives by Multiple Crew Model

Scheduling of Repetitive Projects with Multiple Objectives by Multiple Crew Model

Optimization Study of Construction Repetitive Project Scheduling Based on Big Data Background

This paper proposes the use of LOB method for repetitive project scheduling solution, and the use of branch limit algorithm to optimize LOB resource allocation to provide the best resource distribution scheme for construction projects. The control process types are analyzed and the time parameters of the LOB method are calculated. Introduce the resource constraint problem of repetitive projects, establish the objective function, put forward the relevant constraints of LOB resource allocation, combine the branching strategy, limiting strategy and pruning strategy, and construct the resource allocation process of LOB scheduling based on the branching and limiting algorithm. Select the parameters number of processes ($n$), maximum employable amount of processes ( k j ), and deadline tightness ( θ ), and conduct random generation tests to compare the performance of different LOB scheduling methods. The LOB scheduling schedule problem is described in the context of a construction project example, and the LOB resource allocation problem is solved by the branch-and-bound algorithm to obtain the optimal resource allocation scheme. Calculate the duration of each process after transformation is 12, 23, 13, 17.1, 12, 12. And the end time of the last process is 44.3, which satisfies the contract duration.

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.

Optimization of Tunnel Construction Schedule Considering Soft Logic

Tunnel construction projects are a classic type of repetitive project, and hold a crucial position in the construction industry. The linear scheduling method (LSM) has been in the spotlight in scheduling optimization for repetitive construction projects since it was first proposed. However, the possibility of changing the construction sequence during application is very often overlooked, which is not in line with actual engineering practices. Incorporating soft logic into LSM and considering the characteristics of tunnel construction, we propose an optimization method for the tunnel construction schedule to shorten the duration by opening up an additional working surface. A mixed-integer programming (MIP) model is developed, which considers various constraints, such as construction sequence and work continuity. The exact algorithm and genetic algorithm (GA) are designed via Python, and the validity is verified through practical cases. A comparative analysis was conducted between the two algorithms and their outcomes demonstrates that the method can satisfy the restrictive constraints of tunnel construction projects. In addition, improvement strategies for tunnel construction management are recommended.

ADAPTIVE LOB SCHEDULING FOR OPTIMIZING RESOURCE LEVELING AND CONSUMPTION

Several techniques were developed to improve resource allocation in construction projects, yet few in repetitive construction projects. Accordingly, this research aims at minimizing resource consumption and fluctuations using Line-of-Balance (LOB) repetitive scheduling technique. An optimization model has been developed consisting of three modules: LOB schedule module, resource leveling module, and optimization module. The model helps determine the optimum (a) start time for each activity considering any needed delays to level resources, (b) number of crews travelling from one unit to another, (c) unit to change the number of crews, and (d) the new changed number of crews. Unlike the existing efforts, the developed model provides the capabilities of (a) allowing the change of number of crews of an activity at a certain repetitive unit to increase or decrease the progress rate; and (b) accommodates non-serial repetitive projects to enhance the model’s practicality. Using a pipeline project, the model outperformed the existing LOB-based models in minimizing resource consumption and fluctuations within the desired project duration. This study offers the project planners a useful tool to efficiently utilize their projects’ resources and avoid hidden costs due to inefficient resource utilization on-site as well as overcoming shortage in resource availability.

Resource-constrained repetitive project scheduling with soft logic

PurposeIn repetitive projects, repetition offers more possibilities for activity scheduling at the sub-activity level. However, existing resource-constrained repetitive scheduling problem (RCRSP) models assume that there is only one sequence in performing the sub-activities of each activity, resulting in an inefficient resource allocation. This paper proposes a novel repetitive scheduling model for solving RCRSP with soft logic.Design/methodology/approachIn this paper, a constraint programming model is developed to solve the RCRSP using soft logic, aiming at the possible relationship between parallel execution, orderly execution or partial parallel and partial orderly execution of different sub activities of the same activity in repetitive projects. The proposed model integrated crew assignment strategies and allowed continuous or fragmented execution.FindingsWhen solving RCRSP, it is necessary to take soft logic into account. If managers only consider the fixed logic between sub-activities, they are likely to develop a delayed schedule. The practicality and effectiveness of the model were verified by a housing project based on eight different scenarios. The results showed that the constraint programming model outperformed its equivalent mathematical model in terms of solving speed and solution quality.Originality/valueAvailable studies assume a fixed logic between sub-activities of the same activity in repetitive projects. However, there is no fixed construction sequence between sub-activities for some projects, e.g. hotel renovation projects. Therefore, this paper considers the soft logic relationship between sub-activities and investigates how to make the objective optimal without violating the resource availability constraint.

Optimization of the Cost of Repetitive Construction Projects Using Computerized Iteration Method

This study introduces an iterative scheduling method that combines two approaches for managing repetitive construction projects: the Critical Path Method (CPM) and the Repetitive Scheduling Method (RSM). The primary objective of this study is to demonstrate how optimization techniques can be applied to minimize the cost of construction projects within a defined range, spanning from the shortest to the longest possible project durations. In the shortest project duration (as determined by CPM), all activities are allocated idle times based on precedence constraints, while in the longest duration (as determined by RSM), there is no idle time allocated. To calculate the optimal schedule, a computerized iterative method specifically designed for this purpose considers all possible combinations of activities with and without idle time. The optimum schedule is the one that minimizes the total project cost. The study reveals that by using an Excel spreadsheet, it is feasible to deterministically optimize the cost of repetitive construction projects, achieving the minimum cost. This minimization process can also be implemented as a Python application. Notably, this proposed system provides multiple optimal solutions, enabling managers to select the most suitable one. This advantage distin-guishes it from conventional methods, such as genetic algorithms and other optimization techniques. However, there are some limitations when applying this application, one of which is the maximum capacity available to run the application.

The strategic use of learning in repetitive projects

The strategic use of learning in repetitive projects

Reactive Scheduling for Repetitive Projects Based on Integrated Crew Interruption and Soft Logic Strategies

Reactive Scheduling for Repetitive Projects Based on Integrated Crew Interruption and Soft Logic Strategies

Proactive-reactive repetitive project scheduling method – the concept of risk consideration at the project planning and execution stage

Proactive-reactive repetitive project scheduling method – the concept of risk consideration at the project planning and execution stage

Multimode variable resource-constrained time/cost trade-off problem in repetitive projects with adjustment strategy

Resource availability is the crucial factor of construction project scheduling decision, as it impacts the time and cost of the project. However, traditional researches assume that resource availability is fixed, which does not reflect the actual situation. This article proposes a model for addressing the multimode variable resource-constrained time/cost trade-off problem (Mvrc-DTCTP) in repetitive projects. To better capture the characteristics of repetitive projects, an adjustment strategy is designed to mitigate the impact of work continuity interruptions on idle time. Through simulation analysis, it was found that increasing resource supply can reduce project duration, but it is not directly proportional to cost. This phenomenon further increases the uncertainty in the relationship between duration and cost, inevitably affecting managers’ ability to develop effective scheduling plans. By employing the Mvrc-DTCTP model, project managers can obtain more and better solutions than traditional methods, with shorter duration, and lower total cost. The proposed adjustment strategy results in a 54% reduction in idle time, a $4000 cost reduction and more feasible solutions. Based on calculations for 30 randomly generated cases, the adjustment strategy achieves optimization rates ranging from 24.43% to 84.24%. The adjustment strategy demonstrates the best optimization effect when the resource supply level is moderate.

Optimization Study on Carbon Trading and Constructive Repetitive Project Scheduling in the Context of Internet Era

Abstract This paper constructs a carbon trading market trade-off problem model based on the time-constrained relationship of process families in RSM. By analyzing the repetitive construction project processes, linear, block, and strip processes are refined. The time-constrained relationship between process families in the RSM is studied, and the expression formula is derived. Process continuity and resource continuity in repetitive construction projects are analyzed to reduce the time required to complete a unit of work. The process duration of the project is determined by optimizing the amount of new resources and human resources used. The results show that when the length of the carbon emission interval is at (0.5, 2]t, when the length of the carbon emission interval is small, the role of RSM process time carbon trading price is larger.

Repetitive Projects Scheduling to Minimize Idle Time: A Case Study of Libyan Electricity Infrastructure Projects

Repetitive Projects Scheduling to Minimize Idle Time: A Case Study of Libyan Electricity Infrastructure Projects

Optimizing the number of crews working in parallel and their work sequence to minimize project duration and cost for repetitive construction projects

Scheduling repetitive construction projects poses a significant challenge in optimally utilizing multiple concurrent crews and sequencing their work to minimize project duration and cost. To address this challenge, this study presents the development of a multi-objective scheduling optimization model for repetitive construction projects consisting of three modules. First, a scheduling module ensures the harmonious coordination of multiple concurrent crews for each activity while considering varying productivity rates, work continuity constraints, and project precedence relationships. Second, a cost module incorporates various contractual cost components to enable a thorough evaluation of project costs and provides flexibility to contractors encountering different contract terms. Third, an optimization module utilizes a genetic algorithm to identify optimal combinations of crews working in parallel and their optimal work sequence, to simultaneously minimize project duration and cost. An application example from the literature was analyzed to validate the model and demonstrate its superiority over previous models. The results showed significant reductions of 8% and 0.78% in project duration and overall costs, respectively, compared to previous models. Furthermore, the capabilities of the model were demonstrated through a real-life case study involving a highway development and renovation project, highlighting its practical benefits and effectiveness in a real-world construction scenario.

A Comparison of the Project Management Methodologies PRINCE2 and PMBOK in Managing Repetitive Construction Projects

Nowadays, companies employ various project management (PM) methodologies to ensure that their projects are effective and successful. It is worth knowing that differences in principles and processes of PM methodologies influence the use of different PMs in managing non-repetitive and repetitive construction projects. This paper presents the selection and application of a rational construction PM methodology to a repetitive construction project after a comparison of two PM methodologies, namely Project Management Body of Knowledge (PMBOK) and Projects IN Controlled Environments (PRINCE2). The object of this study is a repetitive anti-corrosion works project for steel structures conducted at Company X. The research was carried out in two steps. First, a quantitative survey of the respondents from companies involved in the management and execution of construction projects was conducted with the aim to identify a rational approach to construction PM. The questionnaire consisted of fourteen closed-ended questions, six of which were generic and eight were PMBOK- and PRINCE2-specific questions. Companies that took part in the quantitative study identified the PRINCE2 project management approach as the most suitable for managing a repetitive construction project. Using the PRINCE2 PM methodology, the repetitive construction project would aim to provide as much information as possible to the project participants, form a team and assign team leaders responsible for the phases, establish a financial plan, a detailed timetable for the execution of the works, a quality control plan, and a plan of responsible persons, and detail the technological sequencing of the works. Second, a quantitative study on the selection of a rational construction project management approach for a repetitive construction project was pursued, and a qualitative assessment of construction project monitoring trends and actions was conducted. The qualitative research was performed using a structured interview method and asking the representatives of different companies X, Y, and Z the same 15 questions. The results of the qualitative research showed that a successful PM depends on the size of the project team, the PM tools and methodologies used, the PM philosophy, and the frequency of monitoring and discussing the project progress.

Scheduling the Work of Multiple Construction Crews Working Concurrently in Repetitive Construction Projects

Scheduling the Work of Multiple Construction Crews Working Concurrently in Repetitive Construction Projects

RESOURCE LEVELLING IN REPETITIVE CONSTRUCTION PROJECTS WITH INTERRUPTIONS: AN INTEGRATED APPROACH

Despite the significance of resource levelling, project managers lack various ways to smooth resource usage fluctuation of a repetitive construction project besides changing resource usage. Tolerating interruptions is an effective way to provide flexibility for a schedule but is ignored when solving resource levelling problems. Therefore, this paper investigates the impacts of interruptions on resource usage fluctuation and develops an integrated approach that simultaneously integrates two scheduling adjusting processes: changing resource usage and tolerating interruptions. In this paper, two interruption conditions are proposed to identify which activities are suitable to be interrupted for smoothing resource usage fluctuation. The traditional resource levelling model is modified to a new scheduling model by incorporating interruptions. A two-stage GA-based scheduling algorithm is developed by integrating changing resource usage and tolerating interruptions. A commonly used pipeline project is adopted to illustrate the steps of the proposed approach and demonstrate its effectiveness and superiority through comparison with previous studies. A large-scale project further verifies the usability of the proposed approach. The results confirmed the feasibility to smooth resource usage fluctuation by interruptions, and the integrated approach can achieve a more competitive resource levelling result.

Building projects with time–cost–quality–environment trade-off optimization using adaptive selection slime mold algorithm

Every project manager deals with various challenges, and almost all tasks have backup plans to ensure efficient success. Therefore, it is essential to manage resources, notably in terms of time, cost, quality, and environmental impact, and this needs to be thoroughly shown. As a result, the adaptive selection slime mold algorithm (ASSMA) is proposed for repetitive projects due to multiple concurrent instances. It is made by merging the tournament selection (TS) method and the slime mold algorithm (SMA) model. The new model’s capabilities are demonstrated using a case study of a rural water pipeline project, and the outcomes of the ASSMA are contrasted with those of the data envelopment analysis (DEA) approach utilized by the previous researcher. Consequently, the ASSMA technique is an effective optimization matching method that can help project managers select the best strategy for a given activity. This study is anticipated to expand significantly and outperform other models by utilizing quality performance metrics.