Site Layout Planning using Nonstructural Fuzzy Decision Support System

Site layout planning can affect productivity and is crucial to project success. However, as construction is heterogeneous in the nature of its organizations, project designs, time constraints, environmental effects, etc., site layout planning for each project becomes unique. Affected by many uncertainties (variables) and variations, site layout planning is a typical multiobjective problem. To facilitate the decision-making process for these problems, a nonstructural fuzzy decision support system (NSFDSS) is proposed. NSFDSS integrates both experts’ judgment and computer decision modeling, making it suitable for the appraisal of complicated construction problems. The system allows assessments based on pairwise comparisons of alternatives using semantic operators that can provide a reliable assessment result even under the condition of insufficient precise information.     

Generic Process Mapping and Simulation Methodology for Integrating Site Layout and Operations Planning in Construction

The present research is intended to address dynamic construction-process simulation methods, with a focus on how to effectively model resource transit among various activity locations in the site system. Following a review of basic simulation paradigms and recent research developments, we propose a new process mapping and simulation methodology for modeling construction operations. The simulation algorithm is presented and the process mapping procedure is illustrated step by step using an earth-moving example featuring technology and resource constraints. It is straightforward to convert the resultant process mapping model describing workflows and resource flows over site locations into a simulation model. A STROBOSCOPE model is formed for the same problem definition to contrast and cross-validate our methodology with the established activity cycle diagram-based modeling approach. One additional case of modeling the concreting site operations by the hoist and barrow method is also given to demonstrate the application of the proposed methodology in practical settings.     

Trade-off between Safety and Cost in Planning Construction Site Layouts

Planning construction site layouts involves identifying the positions of temporary facilities on site, and accordingly it has a significant impact on the safety and efficiency of construction operations. Although available models are capable of minimizing the travel cost of resources on site, they do not consider safety as an important and separate objective in the optimization of site layouts. This paper presents the development of an expanded site layout planning model that is capable of maximizing construction safety and minimizing the travel cost of resources on site, simultaneously. The model incorporates newly developed concepts and performance criteria that enable the quantification of construction safety and travel cost of resources on site. The present model is developed in three main phases: (1) formulating decision variables and optimization objectives in this site layout planning problem; (2) identifying and satisfying all practical constraints in this optimization problem; and (3) implementing the model as a multiobjective genetic algorithm. An application example is analyzed to illustrate the use of the model and demonstrate its capabilities in optimizing construction site layouts and generating optimal trade-offs between safety and travel cost of resources on site.     

Dynamic Site Layout Planning Using Approximate Dynamic Programming

Dynamic site layout planning requires identifying and updating the positions of all temporary construction facilities such as offices, storage areas, and workshops over the entire project duration. Existing models do not guarantee global optimal solutions because they focus on optimizing the planning and layout of successive construction stages in a chronological order, without considering the future implications of layout decisions made in early stages. This paper presents the development of an approximate dynamic programming model that is capable of searching for and identifying global optimal dynamic site layout plans. The model applies the concepts of approximate dynamic programming to estimate the future effects of layout decisions in early stages on future decisions in later stages. The model is developed in three main phases: (1) formulating the decision variables, geometric constraints, and objective function of the dynamic site layout planning problem; (2) modeling the problem using approximate dynamic programming; and (3) implementing and evaluating the performance of the model. An evaluation example is analyzed to illustrate the use of the model and demonstrate its capabilities in generating global optimal solution for dynamic site layout planning of construction projects.     

Optimizing Airport Construction Site Layouts to Minimize Wildlife Hazards

Construction operations in airport expansion projects often attract wildlife species to critical airport traffic areas leading to an increase in the risk of wildlife–aircraft collision accidents. Airport operators and construction planners need to carefully consider and minimize these wildlife hazards during the planning of construction site layouts in order to comply with Federal Aviation Administration recommendations. This paper presents the development of an advanced optimization model for planning airport construction site layouts that is capable of minimizing the hazards of wildlife attractants and minimizing the site layout costs, simultaneously. The model incorporates newly developed concepts and performance criteria that enable (1) quantifying, controlling, and minimizing the hazards of construction-related wildlife attractants near airport traffic areas; and (2) minimizing the travel cost of construction resources and the cost of devices installed to control wildlife on airport construction sites, while complying with all relevant aviation safety constraints. The model is developed using a multiobjective genetic algorithm and an application example is analyzed to demonstrate the use of the model in optimizing airport construction site layouts and its unique capability of generating optimal trade-offs between wildlife control and site layout costs.     

Comparison of Using Mixed-Integer Programming and Genetic Algorithms for Construction Site Facility Layout Planning

The use of modular construction has gained wide acceptance in the industry. For a specific construction facility layout problem such as site precast standardized modular units, it requires the establishment of an on-site precast yard. Arranging the precast facilities within a construction site presents real challenge to site management. This complex task is further augmented with the involvement of several resources and different transport costs. A genetic algorithm (GA) model was developed for the search of a near-optimal layout solution. Another approach using mixed-integer programming (MIP) has been developed to generate optimal facility layout. These two approaches are applied to solve with an example in this paper to demonstrate that the solution quality of MIP outperforms that of GA. Further, another scenario with additional location constraints can also be solved readily by MIP, which, however, if modeled by GA, the solution process would be complicated. The study has highlighted that MIP can perform better than GA in site facility layout problems in which the site facilities and locations can be represented by a set of integer variables.     

Planning and Scheduling Highway Construction

This paper presents a model designed to integrate the planning and scheduling phases of highway construction projects, focusing primarily on the planning aspects. The model automatically generates the work breakdown structure (WBS) and precedence network respecting job logic and stores a list of construction operations typically encountered in highway projects. The generated network can subsequently be modified to suit the unique requirements of the project being considered. An object-oriented model is developed for planning highway construction operations. The model employs resource-driven scheduling in order to suit the repetitive nature of this class of projects. It accounts for (1) resource availability; (2) multiple preceding and succeeding activities; (3) transverse obstructions; (4) activities with varying quantities of work along the highway length; (5) the impact of inclement weather on crew productivity; and (6) the beneficial effect of the learning curve. At the core of the model is a relational database designed to store available resources and their respective unavailability periods. The model enables both: (1) activities executed by own force; and (2) activities subcontracted out. The model is incorporated in a prototype software that operates in the Microsoft Windows environment and generates schedules in both graphical and tabular formats. An example project is analyzed to demonstrate the features of the developed model.     

Automated Recognition of 3D CAD Objects in Site Laser Scans for Project 3D Status Visualization and Performance Control

This paper presents a new approach that allows automated recognition of three-dimensional (3D) computer-aided design (CAD) objects from 3D site laser scans. This approach provides a robust and efficient means to recognize objects in a scene by integrating planning technologies, such as multidimensional CAD modeling, and field technologies, such as 3D laser scanning. Using such an approach, it would be possible to visualize the 3D status of a project and automate some tasks related to project control. These tasks include 3D progress tracking, productivity tracking, and construction dimensional quality assessment and quality control. This paper provides an overview of the developed approach and demonstrates its performance in object recognition and project 3D status visualization, with data collected from a construction job site.     

Areas of Application for 3D and 4D Models on Construction Projects

In recent years more and more construction projects used three-dimensional/four-dimensional (3D/4D) models to support management tasks. However, project managers still struggle with evaluating how the 3D/4D model technology can be most efficiently applied on their specific project. One main reason for this struggle is that an account about how 3D/4D models have been used in the past is missing. This paper offers practitioners and researchers such an account of the application areas of 3D/4D model technologies including the purposes for which these technologies have been applied. The paper qualitatively aggregates the results of 26 case studies of 3D/4D model applications on construction projects to show researchers and practitioners how 3D/4D models have been applied to address project challenges. Using a “project challenge—3D/4D model application” matrix the paper explains each application area and describes why the application has been beneficial to the case study projects. The paper then analyzes the challenges that practitioners have faced with 3D/4D models on the test case projects. The main findings of this analysis are that practitioners on most of the test case projects have used the models for only one application area. The paper suggests that further research on the integration of 3D/4D model technologies into work and business processes of project teams is needed to address this opportunity for a more widespread use of 3D/4D models throughout the lifecycle of a project.     

Computer-Aided Model Generation for Nonlinear Structural Analysis Using a Structural Component Model Database

This paper presents an approach for efficiently building analytical models for nonlinear analysis. The objective has been achieved by establishing structural component model database by collecting various structural component models addressing various structural details. A common data structure and a relational database schema for storing structural component models were proposed in this study. The proposed structural component model database can serve as a decision supporting system for building nonlinear analytical models manually. In addition, the modeling information stored in this database can be presented in XML document format to be parsed and manipulated by computer system for generating nonlinear analytical model in file automatically. A school building database is used as a case study to show the feasibility of automatic modeling for nonlinear analysis using the proposed structural component database. A semiautomatic model generation system was developed to provide an efficient modeling process, which is in the manner of form filling and option selecting on web-based user interfaces, so that the model builder can focus on making engineering decisions. The modeling details are handled automatically by the proposed system based on user selection and setting.     

Formulating Procurement Selection Criteria through Case-Based Reasoning Approach

An appropriate procurement system is a catalyst to the success of a construction project. In practice, the solutions and outcomes of previous procurement selection decisions could be extremely useful in supporting decision making. As a technique that captures and reuses experiential knowledge, case-based reasoning (CBR) has a high potential for modeling the procurement selection decision within a complex dynamic environment. This paper examines the suitability of CBR approaches for procurement selection. The process involved in procurement selection is examined first. A conceptual framework for case-based procurement selection is proposed. The structure of a prototype model on procurement selection criteria (PSC) formulation is presented in this paper. The model applies the CBR approach to procurement criteria selection irrespective of the variability in the characteristics of the client, project, and external environment.     

Minimizing Construction-Related Security Risks during Airport Expansion Projects

Airport expansion projects often require the presence of construction personnel, material, and equipment near airport secure areas/facilities, leading to an increase in the level of risk to airport security. Construction planners and airport operators need to carefully study this challenge and implement active measures in order to minimize construction-related security breaches and comply with all relevant Federal Aviation Administration guidelines. This paper presents the development of an advanced multiobjective optimization model for planning airport construction site layouts that is capable of minimizing construction-related security breaches while simultaneously minimizing site layout costs. The model incorporates newly developed criteria and performance metrics that enable evaluating and maximizing the construction-related security level in operating airports. The model is developed using a multiobjective genetic algorithm, and an application example is analyzed to demonstrate the use of the model and its unique capability of generating a wide spectrum of optimal trade-offs between construction-related airport security and site layout costs.     

Decision Support System for Manufactured Housing Facility Layout

Productivity improvement of manufactured housing (MH) production systems has been a great concern to manufacturers and production managers. Studies show that a typical manufactured housing plant fails to produce at desired capacity and production rate because of several shortcomings. The evaluation of the production system efficiency in the factory is essential for meeting the growing demand of customers with respect to design and size of the housing product. It is imperative to explore alternative layout designs that would be more efficient and productive. A decision support system (DSS) is proposed to assist the user in selecting an efficient layout design matching specified requirements and business constraints. The DSS framework covers interrelated factors of: (1) the market demand; (2) MH organization; (3) MH production process; and (4) MH production planning and facility design. Existing MH factories can utilize simulation and optimization components of the DSS in streamlining their activities and locating then solving potential bottlenecks. Additionally, the DSS can be used in selecting optimal production system layout for new plant design.     

Minimizing Construction-Related Hazards in Airport Expansion Projects

Airport expansion projects often require the presence and movement of construction labor and equipment near critical airport traffic areas. This close proximity between construction activities and airport operations needs to be carefully considered during the planning of construction site layouts in order to minimize and eliminate all potential construction-related hazards to aviation safety. This paper presents the development of a multiobjective optimization model for planning airport construction site layouts that is capable of minimizing construction-related hazards and minimizing site layout costs, simultaneously. The model incorporates newly developed optimization functions and metrics that enable: (1) maximizing the control of hazardous construction debris near airport traffic areas; (2) minimizing site layout costs including the travel cost of construction resources and the cost of debris control measures on airport sites; and (3) satisfying all operational safety constraints required by the federal aviation administration as well as other practical site layout constraints. The model is implemented using a multiobjective genetic algorithm and an application example is analyzed to demonstrate the use of the model and its capabilities in optimizing construction site layouts in airport expansion projects.     

Conflict Resolution in Construction Disputes Using the Graph Model

A formal approach is presented for systematically resolving construction conflicts. Using an actual case study, a decision support system based on the graph model for conflict resolution (GMCR II), is employed to effectively investigate the strategic interactions that took place between an owner and a general contractor concerning the financing of a construction project. The conflict analysis process considers the decision participants, their decision options, and their relative preferences when modeling the dispute. GMCR II is then used to perform an in-depth stability analysis in order to ascertain the possible compromise resolutions or equilibria. In the case study, GMCR II correctly predicts the sequence of decisions that took place in the dispute and furnishes an array of useful strategic insights about the conflict. Moreover, a sensitivity analysis is executed to determine how changes in preferences can affect the equilibrium results. This conflict resolution procedure is useful for both researchers and practitioners to better deal with the dispute-prone nature of the construction industry.     

Applicability of 4D CAD in Civil Engineering Construction: Case Study of a Cable-Stayed Bridge Project

Four-dimensional (4D) computer-aided design (CAD) has been credited with improving construction planning procedures. The integration of three-dimensional CAD with schedule information has enabled the effective detection of design and planning flaws in many construction projects. However, the benefit of 4D CAD has been centered on architectural constructions, as other areas such as civil infrastructure have seldom been the target of 4D CAD application. This paper presents a case study in which a cable-stayed bridge construction was analyzed and modeled using the 4D graphic simulation approach. The cable-stayed bridge was chosen for the case study because it suitably represents the complex nature of modern civil infrastructure. 4D CAD models were developed at three different levels of detail: activity, discrete operation, and continuous operation. The clear definitions of the three levels of detail of 4D CAD and their application results for the cable-stayed bridge are presented herein.     

Web-Based Client Advisory Decision Support System for Design–Builder Prequalification

The design–build procurement route is gaining popularity and being extensively used by many clients. Scrutinizing the capabilities of design–build “candidate” organizations (who submit proposals for prequalification/short listing), is a complex task that demands the evaluation of several quantitative and qualitative attributes. The crucial task of design–builder prequalification needs multidisciplinary expertise that often poses tough challenges to many construction clients. A Hong Kong based cross-sectional research study of various international clients’ design–builder selection approaches unveiled several selection strategies and criteria used; and benchmarked some best practices. Based on such consolidated knowledge, a structured design–builder selection model was developed. The conceptualized frameworks for design–builder prequalification are described in this paper. An overview of the development and preliminary validation of a prototype web-based decision support system for design–builder prequalification is also presented in this paper.     

Entropic Risk Analysis by a High Level Decision Support System for Construction SMEs

The method of entropy has been useful in evaluating inconsistency on human judgments. This paper illustrates an entropy-based decision support system called e-FDSS to the solution of multicriterion risk and decision analysis in projects of construction small and medium enterprises (SMEs). It is optimized and solved by fuzzy logic, entropy, and genetic algorithms. A case study demonstrated the use of entropy in e-FDSS on analyzing multiple risk criteria in the predevelopment stage of SME projects. Survey data studying the degree of impact of selected project risk criteria on different projects were input into the system in order to evaluate the preidentified project risks in an impartial environment. Without taking into account the amount of uncertainty embedded in the evaluation process; the results showed that all decision vectors are indeed full of bias and the deviations of decisions are finally quantified providing a more objective decision and risk assessment profile to the stakeholders of projects in order to search and screen the most profitable projects.     

Theft and Vandalism on Construction Sites

Theft and vandalism on construction sites in the commercial construction industry is a problem that can affect productivity and drain profits. To explore the impact of theft and vandalism in the commercial construction industry, a survey was sent to commercial construction firms to gather information by which the magnitude of the problem of theft and vandalism could be estimated; and to determine what techniques have been successfully used to deter thieves and vandals. The responses were analyzed and several conclusions were developed. Firms engaging in all types of projects are susceptible to theft and vandalism. Theft is more costly to large sized firms ($100 million and over in annual volume of construction work) than smaller firms, but vandalism is more costly for smaller firms. This occurs despite the fact that larger firms use a greater number of measures to combat theft and vandalism on their construction sites. The results should be of particular interest to construction firms that want to reduce the number of theft and vandalism incidents.