Repetitive Construction Projects Research Articles

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.

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.

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.

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.

Application of Linear Scheduling in Water Canal Construction with a Comparison of Critical Path Method

Critical path method (CPM) still remains the most commonly used scheduling technique, despite many studies confirming its shortcomings for scheduling repetitive construction projects. This research evaluated the case study of an alignment-based precast water canal erection project, which was originally planned with CPM and analysed the suitability of using linear scheduling method (LSM) for the same project. The case study project was scheduled using both CPM and LSM tools and the results were compared in terms of estimated total duration and resource cost. The results showed that LSM produced a saving of 10 days in total duration and 20.07% in estimated resource cost over CPM. LSM also proved to be the better tool in terms of other schedule attributes like resource assignment, levelling, visualisation, etc., for alignment-based projects. LSM can be highly efficient for scheduling different types of repetitive construction and offers benefits like better workflow and continuous resource usage.

SCHEDULING REPETITIVE CONSTRUCTION PROJECTS: STRUCTURED LITERATURE REVIEW

Construction projects that involve repetitive operations are often referred to as repetitive construction projects. Scheduling them proves a task more demanding than in the case of projects in other industries. Typical objectives of optimization, a characteristic set of constraints, as well as the schedule’s susceptibility to the propagation of disruptions caused by materializing risks, call for specific scheduling methods. The authors review the literature to summarize the existing repetitive scheduling methods and put forward their classification to identify the method’s aspects needing refinement. This is done to point to directions of further research. The authors hope that this study will contribute to better identification of existing problems in planning repetitive construction projects and faster development of decision support systems, eagerly anticipated by the construction practitioners. Though the focus is on applications to construction projects, the repetitive scheduling methods that account for volatile operating conditions may be of interest to researchers who develop planning techniques for other industries.

Harmonizing construction processes in repetitive construction projects with multiple buildings

One of the main issues of construction scheduling is harmonizing the work of crews that perform repetitive processes. The schedules determine the resource flow and the efficiency of the construction stage. Traditional scheduling tools are not suitable for repetitive projects. Therefore, the authors put forward a deterministic method for harmonizing works in projects to construct a number of buildings with the repetitive processes conducted in non-uniform units. The scheduling objectives are to minimize the overall project duration, the makespan of the buildings, and resource idle time. The relative importance of these criteria is to be decided by the planner. A particle swarm algorithm was employed for optimization. The merits of the method were illustrated by a real-life case: a project to construct an estate of duplex houses.

Developing A Mathematical Model for Planning Repetitive Construction Projects By Using Support Vector Machine Technique

Abstract Each project management system aims to complete the project within its identified objectives: budget, time, and quality. It is achieving the project within the defined deadline that required careful scheduling, that be attained early. Due to the nature of unique repetitive construction projects, time contingency and project uncertainty are necessary for accurate scheduling. It should be integrated and flexible to accommodate the changes without adversely affecting the construction project’s total completion time. Repetitive planning and scheduling methods are more effective and essential. However, they need continuous development because of the evolution of execution methods, essentially based on the repetitive construction projects’ composition of identical production units. This study develops a mathematical model to forecast repetitive construction projects using the Support Vector Machine (SVM) technique. The software (WEKA 3.9.1©2016) has been used in the process of developing the mathematical model. The number of factors affecting the planning and scheduling of the repetitive projects has been identified through a questionnaire that analyzed its results using SPSS V22 software. Three accuracy measurements, correlation coefficient (R), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE), were used to check the mathematical model and to compare the actual values with predicted values. The results showed that the SVM technique was more precise than those calculated by the conventional methods and was found the best generalization with R 97 %, MAE 3.6 %, and RMSE 7 %.

Stochastic scheduling optimization of repetitive construction projects to minimize project duration and cost

Considering risk and uncertainty during the scheduling optimization of repetitive construction projects is a challenging task. This article presents the development of a novel multi-objective stochastic scheduling optimization model for minimizing the expected project duration and cost of repetitive construction projects. The developed model integrated Monte Carlo simulation with a multi-objective genetic algorithm to: (1) consider uncertainties associated with the production rates of the construction crews; and (2) identify an optimal crew formation and crew deployment date for each activity that minimize the project duration and cost. The performance of the developed model was analyzed using a real-life case study that highlighted the novel model capabilities in generating a set of optimal trade-off solutions between expected project duration and cost while considering all uncertainties in crew production rates. These novel capabilities of the developed model enable construction planners to identify and implement an optimal resource utilization plan that account for inherent project risks.

Tradeoff time cost quality in repetitive construction project using fuzzy logic approach and symbiotic organism search algorithm

Time cost and quality are three important factors in planning and controlling construction projects. Getting these factors in balance, which minimizes the project duration, the total project cost, and maximizes the total quality could define the success of a construction project. Aside from planning and estimating the project properly, a consideration of uncertainty while implementing the project is needed to represent a more realistic outcome for time, cost, and quality trade-off (TCQT) problem in construction projects. In this paper, fuzzy logic is utilized to model the uncertainty embedding α-cut approach to see the effect of the uncertainty on the time, cost, and quality of the project. Then multi-objective Symbiotic Organism Search (SOS) algorithm is applied to find a set of the optimal solution in different uncertainty levels and provide the project manager several possible actions to implement the project. Two numerical case studies of a repetitive construction project were analyzed to see the effectiveness of the model and its capability to solve the TCQT problem in the construction project. The results showed that the proposed model is powerful to explore the solution for the shortest project duration with minimum incurred cost and high overall quality in the construction project. In comparison to the other widely used methods and other algorithms, the proposed model is proven to be effective and competitive in solving the TCQT problem.

Multiobjective Optimization Model for Planning Repetitive Construction Projects

AbstractMinimizing the duration of repetitive construction projects such as high-rise buildings and highway construction often requires interrupting the work continuity of construction crews and/or...

A novel multiple objective whale optimization for time-cost-quality tradeoff in non-unit repetitive projects

Project managers are the ones who struggle to complete the project with the shortest possible time, the least amount of costs and, the highest quality. The primary objective in the planning stage of the project management process is to identify the most suitable schedule from provided time–cost-quality curve. Scheduling of construction repetitive projects assumes the same production and hard logic between units. This study proposes a free-parameter multiple objective whale optimization (MOWO) to tradeoff the time, cost and, quality factors in non-unit repetitive projects (NRP). An external scheduling system shall consider project activities dependencies, multiple crew assignments, and soft logic in units to calculate project duration, cost and, quality. A construction case study was used to examine MOWO performance. Furthermore, some broadly recognized multiple objective evolutionary algorithms are employed to compare with the proposed algorithm. Result comparison points out that MOWO attained the best optimization outcomes in handling the time-cost-quality tradeoff in non-unit repetitive construction projects. Highlights This study presents an advanced multiple optimization algorithm MOWO. A scheduling subsystem is proposed to enable TCQ tradeoff in non-unit repetitive projects. MOWO is applied to solve TCQ for non-unit repetitive construction projects. The model performance is demonstrated in the experimental results.

Linear Optimization Model to Minimize Total Cost of Repetitive Construction Projects and Identify Order of Units

AbstractThis study developed a linear optimization model for scheduling repetitive construction projects with varying quantities of work in repetitive units. The model provides new capabilities tha...

Profit optimization for multi-mode repetitive construction project with cash flows using metaheuristics

The article presents the profit optimization model for multi-unit construction projects. Such projects constitute a special case of repetitive projects and are common in residential, commercial, and industrial construction projects. Due to the specific character of construction works, schedules of such projects should take into account many different aspects, including durations and costs of construction works, the possibility of selecting alternative execution modes, and specific restrictions (e.g., deadlines for the completion of units imposed by the investor). To solve the NP-hard problem of choosing the order of units’ construction and the best variants of works, the authors used metaheuristic algorithms (simulated annealing and genetic search). The objective function in the presented optimization model was the total profit of the contractor determined on the basis of the mathematical programming model. This model takes into account monthly cash flows subject to direct and indirect costs, penalties for missing deadlines, costs of work group discontinuities, and borrowing losses. The presented problem is very important for maintaining a good financial condition of the enterprise carrying out construction projects. In the article, an experimental analysis of the proposed method of solving the optimization task was carried out in a model that showed high efficiency in obtaining suboptimal solutions. In addition, the operation of the proposed model has been presented on a calculation example. The results obtained in it are fully satisfying.

Modeling of CPM/LOB integrated Scheduling Technique for Repetitive Construction Projects: Case of Multiple-Crews with Fuzzy Time Data

Project scheduling provides a good insight for the manager to complete the project on time. Project scheduling gives complete timing analysis of activities involved and identifies the critical ones. Critical Path Method (CPM) is the most widely used in planning and scheduling method for traditional (non-repetitive) projects to determine the critical path which determines the minimum completion time of a project.Some construction projects consist of several similar or identical units, which are called repetitive projects. LOB technique has some drawbacks such inability to generate a clear critical path of the project schedule and calculating the total float because it is a graphical technique. LOB used for scheduling repetitive typical projects because this technique considered work continuity and resource availability constraints to avoid unnecessary crew idle time.Some of the previous studies have been made to combine the benefits of CPM and LOB techniques in planning and scheduling repetitive construction projects, so, there is a model that was developed for this objective (schedule repetitive projects in an easy non-graphical manner). But, in real life, more conditions contributed to varying activity duration. Thus, the duration of project activities contains some sort of uncertainty affecting the estimating of project duration. Previous studies used fuzzy set theory instead of probability theory for quantifying the uncertainty associated with the duration of project activities.In this paper, a developed integrated model of CPM and LOB with fuzzy time data for scheduling repetitive projects is presented. The developed model provides a new technique to schedule repetitive projects with fuzzy time data in an easy non-graphical manner.

Optimizing the scheduling of crew deployments in repetitive construction projects under uncertainty

PurposeThis paper presents the development of a novel model for optimizing the scheduling of crew deployments in repetitive construction projects while considering uncertainty in crew production rates.Design/methodology/approachThe model computations are performed in two modules: (1) simulation module that integrates Monte Carlo simulation and a resource-driven scheduling technique to calculate the earliest crew deployment dates for all activities that fully comply with crew work continuity while considering uncertainty; and (2) optimization module that utilizes genetic algorithms to search for and identify optimal crew deployment plans that provide optimal trade-offs between project duration and crew deployment plan cost.FindingsA real-life example of street renovation is analyzed to illustrate the use of the model and demonstrate its capabilities in optimizing the stochastic scheduling of crew deployments in repetitive construction projects.Originality/valueThe original contribution of this research is creating a novel multiobjective stochastic scheduling optimization model for both serial and nonserial repetitive construction projects that is capable of identifying an optimal crew deployment plan that simultaneously minimizes project duration and crew deployment cost.