Resources In Construction Projects Research Articles

Application of Improved Artificial Immune System Algorithm Based on Applied Mathematics for Optimization of Manpower Allocation in Construction Engineering

The outbreak of the COVID-19 pandemic has led construction companies to prioritize the intelligent and optimal scheduling of human resources in construction projects to reduce costs. This study addresses the problem of heterogeneity in human resource scheduling in construction projects, presents a mathematical model with generic human resources as an example, proposes an improved artificial immune system (NAIS) algorithm to solve the problem, and verifies its effectiveness. Experimental results show that the NAIS algorithm achieves the optimal duration of 9 days in just 2 s using the Matrix Laboratory (MATLAB), which is significantly faster than mathematical optimization technique software (CPLEX), thus confirming the feasibility of the NAIS algorithm. Additionally, the average PD values for the NAIS algorithm, calculated for different worker counts, skills, and the number of tasks, were lower compared to the comparison algorithm. Overall, the NAIS algorithm effectively addresses the heterogeneous problem of human resource scheduling in construction projects with multiple modes, thereby optimizing construction engineering labor allocation.

Space–Time–Workforce Visualization and Conditional Capacity Synthesis in Uncertainty

Workspace, project duration, and workforce are three critical resources for construction projects. Project managers need to expend time and effort reviewing, comprehending, and coordinating these resources. However, the space–time–workforce interactions and their impact on decision-making in project scheduling are not fully known. Therefore, the objectives of this research were to understand the impact of workforce shifts on space, time, and labor cost performances, develop a three-dimensional (3D) visualization tool to reveal activity-level resource dynamics, and associate the risk aftermath with the occurrence probability to balance subjective risk tolerance and objective system reliability. This research developed a simulation model based on a case project to compare the workflow of five major specialty trades (i.e., bar placer, carpenter, scaffolder, pipefitter, and concreter) in 267 scenarios. A resource-oriented 3D visualization tool was developed to help project managers monitor project schedules. The research established a risk control framework using value-at-risk (VaR) and conditional value-at-risk (CVaR) approaches to associate extreme outcomes with their occurrence probability. Simulation results indicated that pipefitters significantly affected workspace overlap, whereas bar placers and carpenters predominantly impacted project duration. The scholarly contributions are (1) the creation of an intelligent system to generate a project schedule from workforce assignments specified by project managers, (2) development of a tool to visualize the three-way resource dynamics of workforce, time, and space on a 3D model for all possible scenarios, and (3) development of a framework for project managers to balance planning strategies between subjective risk tolerance and objective system reliability. This research provides project managers with a dynamic 3D visualization of space, time, and workforce utilization and interaction in uncertain environments, further facilitating reliable project scheduling decision-making.

Estimating labor resource requirements in construction projects using machine learning

PurposeExisting labor estimation models typically consider only certain construction project types or specific influencing factors. These models are focused on quantifying the total labor hours required, while the utilization rate of the labor during the project is not usually accounted for. This study aims to develop a novel machine learning model to predict the time series of labor resource utilization rate at the work package level.Design/methodology/approachMore than 250 construction work packages collected over a two-year period are used to identify the main contributing factors affecting labor resource requirements. Also, a novel machine learning algorithm – Recurrent Neural Network (RNN) – is adopted to develop a forecasting model that can predict the utilization of labor resources over time.FindingsThis paper presents a robust machine learning approach for predicting labor resources’ utilization rates in construction projects based on the identified contributing factors. The machine learning approach is found to result in a reliable time series forecasting model that uses the RNN algorithm. The proposed model indicates the capability of machine learning algorithms in facilitating the traditional challenges in construction industry.Originality/valueThe findings point to the suitability of state-of-the-art machine learning techniques for developing predictive models to forecast the utilization rate of labor resources in construction projects, as well as for supporting project managers by providing forecasting tool for labor estimations at the work package level before detailed activity schedules have been generated. Accordingly, the proposed approach facilitates resource allocation and enables prioritization of available resources to enhance the overall performance of projects.

Optimized scheduling of resource-constraints in projects for smart construction

In real-life applications, resources in construction projects are always limited. It is of great practical importance to shorten the project duration by using intelligent models (i.e., evolutionary computations such as genetic algorithm (GA) and particle swarm optimization (PSO) to make the construction process reasonable considering the limited resources. However, in the general EC-based model, for example, PSO easily falls into a local optimum when solving the problem of limited resources and the shortest period in scheduling a large network. This paper proposes two PSO-based models, which are resource-constrained adaptive particle swarm optimization (RC-APSO) and an input-adaptive particle swarm optimization (iRC-APSO) to respectively solve the static and dynamic situations of resource-constraint problems. The RC-APSO uses adaptive heuristic particle swarm optimization (AHPSO) to solve the limited resource and shortest duration problem based on the analysis of the constraints of process resources, time limits, and logic. The iRC-APSO method is a combination of AHPSO and network scheduling and is used to solve the proposed dynamic resource minimum duration problem model. From the experimental results, the probability of obtaining the shortest duration of the RC-APSO is higher than that of the genetic PSO and GA models, and the accuracy and stability of the algorithm are significantly improved compared with the other two algorithms, providing a new method for solving the resource-constrained shortest duration problem. In addition, the computational results show that iRC-APSO can obtain the shortest time constraint and the design scheme after each delay, which is more valuable than the static problem for practical project planning.

Principles of Management Application in Building Construction Projects: Perspectives of Project Managers’

One of the most crucial factors to consider when setting up and managing organizational activities is the application of management principles. Most of the time, organizational failure is attributed to either as a violation of management principles or an organization's inability to establish this precedent in the running of its day-to-day activities. This paper, therefore, focused on the application of the management principles of Henri Fayol in the management of human resources for construction projects. The study utilized a descriptive design using a survey study and explorative design through a literature search. Relevant literature was reviewed to identify management principles for the design of the questionnaire. The population is the core building professionals working as project managers in a construction site of three tertiary institutions in Bauchi. Forty-five (45) questionnaires were distributed and successfully filled and retrieved. SPSS software was used for the analysis. The study used descriptive statistics and the Kruskal-Wallis test for the analysis. The results show that the majority of the respondents (80 %) acknowledged the importance of these principles to the construction industry in the management of human resources in the construction site. Also, the findings revealed that project managers always used most of these principles in the management of human resources in the construction site. Although, lack of planning and motivation, non-adherence to principles and standards, clashes of interest and corruption revealed as top challenges of its implementation on construction site. The finding concludes that the more the respondent works longer on construction sites, the higher the application of these principles in managing human resources on sites.

Simulation-Based Positioning of Circular Economy Manager’s Skills in Construction Projects

Circular economy (CE) is an emerging economic model based on the endless circulation flow of resources creating additional value. In temporary organizations such as construction projects, all administrative decisions are crucial for final success. One of the ideas is to enroll a circular economy manager (CEMR) and put him in an organizational structure. Implementation of the CE concept should be the effort of the entire project team. However, actions specific to the innovative nature of the procedures related to the CE in construction projects require additional support. It can be provided by professionals who can adapt a wide spectrum of knowledge to be used for promoting CE in the execution of construction processes. CEMRs can play the role of patrons of the CE issues because they support project managers in saving material resources in construction projects. The symmetry between visible outcomes of the CE idea and the employment of an extra manager has contributed to the development of the CEMR selection criteria model. However, effective recruitment for such a post may be a bit complicated for decision-makers, especially when CE is still enigmatic, as its procedures are quite undiscovered. All in all, the multi-criteria decision-making problem forces one to prepare the list of selection criteria and to rank them according to status in the hierarchy. This article shows prioritized criteria for selecting the CEMR based on the advanced literature review concluded after several expert-based reviews and calculated after some Monte Carlo simulations. The main purpose of this article is to help decision-makers in construction projects to perform a reliable recruitment process.

A risk-cost optimization model for selecting human resources in construction projects

One of the solutions for the reduction of the risk of human resource selection in construction projects is to employ specialized people, but this approach imposes tremendous costs because productive people have a high cost of employment. This study provides a model for employing human resources in construction projects with the risk-cost optimization approach. This work, through a review of previous studies, identified several risks in human resource selection that were prioritized in this study by using a questionnaire. The risk-cost rate of each candidate was determined using one of the multi-criteria decision making methods named additive-veto. Finally, the optimization model was developed using the zero–one non-linear programming approach. One of the innovations of this research was to optimize the risk of employees around the organization’s tolerable level of risk rather than reducing risk. The results showed that the selection of human resources based on the model could reduce to a large extent the risk-cost rate.

BIM-based draft schedule generation in reinforced concrete-framed buildings

Purpose Project schedules have a vital role in the effective management of time, cost, scope and resources in construction projects, and creating schedules requires schedulers with construction knowledge and experience. The increase in the complexity of building projects and the emergence of building information modeling (BIM) in the architecture, engineering and construction industry have encouraged researchers to explore BIM capabilities for automated schedule generation. The scope and capabilities of the developed systems, however, are limited and the link between design and scheduling is still underdeveloped. This paper aims to investigate methods to develop a BIM-based framework to automatically generate schedules for concrete-framed buildings. Design/methodology/approach This system first extracts the required data from the building information model, including elements’ dimensions, quantities, spatial information, materials and other related attributes. It then applies construction rules, prior knowledge and production rate data to create project work-packages, calculate their durations and determine their relationships. Finally, it organizes these results into a schedule using project management software. Findings This system provides an automated and easy-to-use approach to generate schedules for concrete-framed buildings that are modeled in a BIM platform. It provides two schedules for each project, both a sequential and an overlapped solution, which the schedulers can modify into a practical schedule based on conditions and available resources. Originality/value This research project presents an innovative approach to use BIM-based attributes of structural elements to develop list of work-packages and estimate their durations, and then it uses a combination of rule-based and case-based reasoning to generate the schedules.

Optimization model for construction project resource leveling using a novel modified symbiotic organisms search

In the construction industry, determining project schedules has become one of the most critical subjects among project managers. These schedules oftentimes result in significant resource fluctuations that are costly and impractical for the construction company. Thus, construction managers are required to adjust the resource profile through a resource leveling process. In this paper, a novel optimization model is presented for resource leveling, called the “modified symbiotic organisms search” (MSOS). MSOS is developed based on the standard symbiotic organisms search, but with an improvement in the parasitism phase to better tackle complex optimization problems. A case study is employed to investigate the performance of the proposed optimization model in coping with the resource leveling problem. The experimental results show that the proposed model can find a better quality solution in comparison with existing optimization models.

FUZZY CLUSTERING CHAOTIC-BASED DIFFERENTIAL EVOLUTION FOR RESOURCE LEVELING IN CONSTRUCTION PROJECTS

Project scheduling is an important part of project planning in many management companies. Resource lev­eling problem describes the process of reducing the fluctuations in resource usage over the project duration. The goal of resource leveling is to minimize the incremental demands that cause fluctuations of resources, and thus avoid unde­sirable cyclic hiring and firing during project execution. In this research, a novel optimization model, named as Fuzzy Clustering Chaotic-based Differential Evolution for solving Resource leveling (FCDE-RL), is introduced. Fuzzy Cluster­ing Chaotic-based Differential Evolution (FCDE) is developed by integrating original Differential Evolution with fuzzy c-means clustering and chaotic techniques to tackle complex optimization problems. Chaotic was exploited to prevent the optimization algorithm from premature convergence. Meanwhile, fuzzy c-means clustering acts as several multi-par­ent crossover operators to utilize the information of the population efficiently to enhance the convergence. Experimental results revealed that the new optimization model is a promising alternative to assist project managers in dealing with construction project resource leveling.

Investigation of the Case-based Reasoning Retrieval Process to Estimate Resources in Construction Projects

Case-based reasoning (CBR) is a methodology that is seeing increasing use to make predictions during the early phases of a project. It allows estimators to exploit existing knowledge to make predictions that are considerably better than without its use. All CBR, however, is not identical, and variations in how CBR is done can affect the accuracy of the predictions. One particular area of sensitivity is the retrieval phase, i.e. the way in which the CBR determines the closeness between the new and the existing cases.In this paper, CBR is used to make estimates of resources for construction projects, and the use of the nearest neighbor technique to identify the similarity for the retrieval phase to predict the construction material quantities (CMQs) in concrete structures is investigated. Two types of distances, i.e. 1) the City-block distance and 2) the Euclidean distance, and four different types of weights, based on regression analysis and feature counting, to account for the relative importance of the different parameters, are investigated. The four different types of weights used were 1) the adjusted unstandardized coefficients from the regression models, 2) the unadjusted unstandardized coefficients from the regression models, 3) the standardized coefficients from the regression models, and 4) equal weights (i.e., feature counting), in which the weights applied are 1/k, and k is the number of parameter being compared to determine the distance.The mean absolute percentage error (MAPE) was used to evaluate each combination investigated. It was found that for a similarity threshold of 90%, the CBR methodology using the City-block distance with the adjusted unstandardized coefficients from the regression analysis models using the transformed (LN) dataset as weights, gave the best results, with a MAPE of 8.16%. The worst results were obtained from the CBR methodology using the Euclidean distance with feature counting weights, with a MAPE of 28.40%.

Reducing the use of resources in medium-sized Swedish construction enterprises: production managers’ views

What construction firms do—and do not do—to reduce the use of resources in construction projects is explored by adopting production managers’ views of their firms’ onsite activities. A literature review and empirical data are combined; 15 production managers have been asked how they perceived their company’s compliance with 31 recommendations to reduce the use of resources. The managers perceived their firms to primarily focus on identifying their customers’ real needs, stimulating employees to undertake further education, and striving for long-term customer–supplier relationships. In contrast, they perceived that less attention was directed to making use of all of the week’s hours, to supporting their main suppliers in their development, and planning feedback and training after project completion. The use of resources is examined by focusing on the perceived low priority given to gathering information and knowledge, as well as to reducing time and the need for long-term relationships with customers in contrast to short-term relationships with suppliers. The managers adopted a project-specific approach mainly to the use of material resources. A more holistic view of resources could enable the development of novel solutions in construction.

Towards improving construction labor productivity and projects’ performance

Proper management of resources in construction projects can yield substantial savings in time and cost. As construction is a labor-intensive industry, this paper focuses on labor productivity in the construction industry. This study considers the current state-of-the-art issues relevant to this subject. It covers the construction labor productivity definitions, aspects, measurements, factors affecting it, different techniques used for measuring it and modeling techniques. The main outcome from the literature is that there is no standard definition of productivity. This study provides a guide for necessary steps required to improve construction labor productivity and consequently, the project performance. It can help improve the overall performance of construction projects through the implementation of the concept of benchmarks. Also, it gives an up to date concept of loss of productivity measurement for construction productivity claims. Two major case studies, from the literature, are presented to show construction labor productivity rates, factors affecting construction labor productivity and how to improve it.

A theory of optimized resource allocation from systems perspectives

AbstractA construction project is an example of a complex systems engineering problem. In this paper, we have characterized a construction project in the context of the theory of six forces on the factors of production. This new approach was defined by giving consideration to the characteristics of the construction project's resource allocation. An economic efficiency index was also used to assess resource allocation of a construction project. Based on this approach, a theory of optimized resource allocation of the construction project is proposed. Copyright © 2009 John Wiley & Sons, Ltd.

Application of AHP in improving construction productivity from a management perspective

Poor productivity of construction workers is one of the major causes of cost overruns and schedule slippages in construction projects. Anecdotal evidence suggests that workers' attitudes towards higher productivity may not be limited to purely financial rewards, but inherently linked to many other latent factors. Some building construction projects in Melbourne are compared to each other to ascertain the factors that influence productivity. The factors and their relative importance impacting on workers' productivity are investigated by using a structured questionnaire survey approach. The survey was formulated with 72 questions covering three broad categories, namely (1) project planning; (2) incentives/disincentives; and (3) job satisfaction. Perceived best practices that impact on improvement of productivity on site were identified from 19 targeted experts. Analytical hierarchy process shows that the biggest influences on productivity are planning and programming. The outcome of this study should assist management decisions in determining the effect on productivity and suggest possible improvements to establish the appropriate management procedures for most productive use of labour resources in construction projects.

FOUNDATIONS OF ECONOMIC THINKING AS A TOOL TO CONTROL CONSTRUCTION AND BUILDING PROJECTS

Due to the state 's tendency to enter into various development projects and the establishmentof a group of new cities. Which requires constant dependence on the construction andBuilding sector. Which is considered one of the most important sectors affecting the nationaleconomy, which is represented in projects in various fields. which use multiple resources suchas (Land, capital, labor, materials), which are rare. that requires careful study of these projectsand work to provide resources for these projects and the exploitation of these resources toensure the success of these projects. Therefore, the research works on using the bases ofeconomic thinking and benefiting from them Access determinants within the construction andbuilding projects. Working on ensuring the economic success of these projects and theutilization of available resources to the fullest. The theoretical study of the stages ofconstruction and Building projects to developthese determinants. Then an analytical study of the projects (Stadium Borg Al Arab - CairoFestival City Center) to assess the determinants of economic thinking within these projects.To reach the conclusion of the most important results and make recommendations that helpsto provide resources for construction projects. نظرا لتوجة الدولة في الدخول في مشروعات تنمية متنوعة و انشاء مجموعة من المدن الجديدة. الامر الذي يستوجبالاعتماد المستمر على قطاع التشييد و البناء. الذي يعتبر احد اھم القطاعات المؤثرة علي الاقتصاد القومي و المتمثل فيمشروعات في مختلف المجالات. والتي تستخدم فيھا موارد متعددة مثل ( الارض – راس المال – العمالة – المواد ) التيتتسم بالندرة. مما يستوجب دراسة متأنية لتلک المشروعات و العمل علي توفير الموارد الازمة لتلک المشروعات و حسناستغلال تلک الموارد لضمان نجاح تلک المشروعات. لذلک يعمل البحث على استخدام اسس التفکير الاقتصادي و الاستفادةمنھا في الوصول لمحددات داخل مشروعات التشييد و البناء لضمان نجاح تلک المشروعات اقتصاديا. والعمل علىاستغلال الموارد المتاحة علي اکمل وجة .تعمل الدراسة النظرية لمراحل مشروعات التشييد و البناء المختلفة لوضع تلک المحددات. ثم ياتي بعد ذلک دراسةتحليلية لمشروعات ( استاد برج العرب – کايرو فيستيفال سيتي المرکز التجاري ) لتقييم محددات اسس التفکير الاقتصاديداخل تلک المشروعات. من ثم الوصول الى استنتاج اھم النتائج و وضع التوصيات التي بدورھا تساعد في توفير المواردلمشروعات التشييد والبناء. بالتالى نجاح المشروع اقتصاديا مما يعود بالنفع علي الاقتصاد القومي

Aptitude development of civil engineers for the management of human resources in construction projects

The paper analyses the singular role human resource management (HRM) plays within the context of construction management, where it differs significantly from its application in other disciplines. A synthesis of HRM research work, in general and in the construction industry in particular, combined with the writer's experience in developing and teaching specialized HRM courses in the civil engineering faculties of two universities, leads to the conclusion that: prospective construction project managers must receive HRM training in appreciably greater scope and depth than is given in most civil engineering schools today; and the peculiar environmental conditions and technology prevalent in construction warrant a specialized adaptation of HRM skills. A syllabus is outlined and discussed.