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.     

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.     

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.     

Computer-Aided Site Layout Planning

This paper presents an interactive computer-aided site layout model to support site planning in a computer-aided design (CAD) environment and expands upon a model presented earlier by the writers. The developed model performs its task at two levels: Site representation, and site space analysis and allocation. The site representation is carried out using an open architecture supported by object-based concepts. The model offers three tiers of objects: (1) site objects, (2) construction objects, and (3) constraint objects. This structure facilitates the creation of new objects and reuse of domain knowledge, which allows for the gradual expansion and enrichment of the model’s knowledge base. At the space analysis and allocation level, the model introduces a geometric reasoning approach to analyze site space for finding an optimum or near-optimum location for facilities. This feature facilitates easy visualization of the site planning process and encourages user participation. The model is structured in three main modules: Database, Project Module, and Layout Control Module. The functionality of each module, along with their interconnectivity is described. The model is implemented using Visual Basic for Applications in AutoCAD environment and Microsoft Access. A numerical example of an actual site layout is presented to illustrate the functionality of the developed model.     

Conjoining MMAS to GA to Solve Construction Site Layout Planning Problem

An optimal construction site layout planning (CSLP) is vital for project management. It can reduce the transportation flows and thus the costs of a project. Genetic algorithm (GA) is the most used algorithm to solve site layout problems, but randomly generated initial population in GA will decrease solution quality. Max-min ant system (MMAS) can offer a better initial population than the randomly generated initial population at the beginning of GA. In this study, a modified GA (MMAS-GA) formed by conjoining MMAS to the step of initialization of GA is proposed to solve CSLP problems. In order to reveal the computational capability of MMAS-GA to solve CSLP problems, the results of MMAS-GA and traditional GA are compared by solving an equal-area CSLP problem. The results showed that the proposed MMAS-GA algorithm provided a better optimal solution under the objective function of minimizing the transportation flows between the site facilities. The proposed MMAS-GA algorithm could assist project managers and planners to design optimal construction site layout, and thus to reduce construction costs.     

Integration of Construction As-Built Data Via Laser Scanning with Geotechnical Monitoring of Urban Excavation

The demand for urban underground space has been increasing in the past decades to create living space and to avoid traffic congestion. A critical concern during the design and development of the underground space is the influence of construction-related ground movements on neighboring facilities and utilities. Currently, engineers can estimate ground movements using a combination of semiempirical methods and numerical model simulation. However, these advanced analyses require accurate as-built construction staging data, which most projects lack. The traditional approach of collecting construction-staging data is both labor intensive and time consuming. This paper explores the use of three-dimensional laser scanning technology to accurately capture construction activities during development of an urban excavation. The paper describes the planning, execution, and data processing phases of collecting accurate construction as-built staging information over a period of 4?months at an urban excavation site in Evanston, Ill. The resulting data provide an unprecedented level of detail on the as-built site conditions and provide much needed information to civil engineering disciplines involved in an urban excavation including construction management and structural and geotechnical engineering.     

Optimal Construction Site Layout Considering Safety and Environmental Aspects

A good site layout is vital to ensure the safety of the working environment and effective and efficient operations. Site layout planning has significant impacts on productivity, costs, and duration of construction. Construction site layout planning involves identifying, sizing, and positioning temporary and permanent facilities within the boundary of the construction site. Site layout planning can be viewed as a complex optimization problem. Although construction site layout planning is a critical process, systematical analysis of this problem is always difficult because of the existence of a vast number of trades and interrelated planning constraints. The problem has been solved using two distinct approaches: Optimization techniques and heuristics methods. Mathematical optimization procedures have been developed to produce optimal solutions, but they are only applicable for small-size problems. Artificial intelligent techniques have been used practically to handle real-life problems. On the other hand, heuristic methods have been used to produce good but not optimal solutions for large problems. In this paper, an optimization model has been developed for solving the site layout planning problem considering safety and environmental issues and actual distance between facilities. Genetic algorithms are used as an optimization bed for the developed model. In order to validate the performance of the developed model, a real-life construction project was tested. The obtained results proved that satisfactory solutions were obtained.     

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.     

Optimizing Material Procurement and Storage on Construction Sites

Efficient planning of materials procurement and storage on construction sites can lead to significant improvements in construction productivity and project profitability. Existing research studies focus on material procurement and storage layout as two separate planning tasks without considering their critical and mutual interdependencies. This paper presents the development of a new optimization model for construction logistics planning that is capable of simultaneously integrating and optimizing the critical planning decisions of material procurement and material storage on construction sites. The model utilizes genetic algorithms to minimize construction logistics costs that cover material ordering, financing, stock-out, and layout costs. The model incorporates newly developed algorithms to estimate the impact of potential material shortages on-site because of late delivery on project delays and stock-out costs. An application example is analyzed to demonstrate the capabilities of the construction logistics planning model in simultaneously optimizing material procurement decisions and storage layout plans.     

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.     

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.     

Materials Handling System Simulation in Precast Viaduct Construction: Modeling, Analysis, and Implementation

The interactive, complicated system environment of a construction site renders conventional site layout planning and scheduling techniques to be inadequate in coping with materials handling system design in construction. In this paper, we present a university-industry joint endeavor for improving the effectiveness of the materials handling system on a precast viaduct construction project in Hong Kong by implementing the simplified discrete-event simulation approach (SDESA) along with its computer platform resulting from recent research. How to apply the simulation methodology of SDESA is elaborated step by step. Particular emphasis is placed on procedures of establishing a simulation model, validation of the simulation model, design of simulation experiments, and analysis of simulation results. With process flowchart, site layout plan, and process animation produced in a view-centric simulation environment, it is straightforward to establish, validate, and communicate the operations simulation. The research team convinced the project director, as well as field managers, of the functionality and effectiveness of operations simulation. The knowledge derived from simulation added to experiences of site managers in materials handling system design. With the aid of simulation, even junior engineers would be capable and confident to draw up an actionable construction plan that would lead to enhancement of cost effectiveness and productivity in the field.     

Performance Evaluation of Construction Enterprise Resource Planning Systems

To successfully evaluate investments related to integrated information management in the construction industry, causal loop diagramming was used to depict the qualitative system dynamics model for the study of the dynamics of construction enterprise resource planning systems (C-ERP). With the aid of system dynamics principles, together with literature review and two case studies, the major variables that influence the successful evaluation of C-ERP in the construction industry were evaluated. The major variables identified were validated with data from a survey. The validation procedure quantified associations between variables and perceived benefits from C-ERP stakeholders of construction-related firms. The model described in this paper aims at providing a holistic understanding of the C-ERP dynamics in construction. With this model, researchers and industry practitioners can develop an insight into C-ERP investments in practice.     

工程现场管理对工程造价影响的研究

施工现场不仅是建筑企业最主要的战场,也是建筑企业的经济目标实现的场所。因此,必须加强工程项目的现场管理。只有这样才能不断地增强施工现场的管理能力,确保工程的质量,节约成本支出以及缩短工期。文章结合笔者多年工作经验,就工程现场管理对工程造价的影响做进一步的研究分析。     

Optimal Lighting Arrangements for Nighttime Highway Construction Projects

This paper presents a decision support system for optimizing temporary lighting arrangements in nighttime highway construction projects. The system is developed as a multiobjective genetic algorithm that is capable of: (1) maximizing average illuminance on construction sites; (2) maximizing lighting uniformity in the work zone; (3) minimizing glare to workers and road users; and (4) minimizing lighting costs. The system is designed to support decision makers in their search for practical lighting arrangements that provide various tradeoffs among these four conflicting objectives. Five decision variables are optimized in the present system, namely: number of lighting equipment, equipment positioning, mounting height, aiming angle, and rotation angle. The system is also designed to consider and satisfy all practical constraints that can be encountered in this lighting design problem. An application example is analyzed to illustrate the use of the system and demonstrate its capabilities in generating near optimal and practical lighting arrangements for nighttime highway construction projects.     

Field Experiments to Evaluate and Control Light Tower Glare in Nighttime Work Zones

An increasing volume of highway repair and construction work is being performed during the off-peak nighttime hours to mitigate the impact of construction-related daytime traffic congestions and shorten the duration of construction operations. The utilization and placement of light towers to illuminate the work zone in this type of construction can cause harmful levels of glare for both drivers and construction workers. This paper presents the results of field experiments which were conducted to (1) study the levels of glare and lighting performance generated by light towers in and around nighttime work zones; (2) analyze the combined impact of the light tower set up parameters including its height as well as its aiming and rotation angles on glare and lighting performance; and (3) provide practical recommendations to reduce and control lighting glare in and around nighttime work zones. The results of these experiments confirm that the set up of light towers has a significant impact on glare and therefore it should be carefully designed and executed on nighttime highway construction projects to ensure the safety of the traveling public as well as construction workers.     

EvoSite: Evolution-Based Model for Site Layout Planning

Appropriate site layout of temporary facilities is crucial for enhancing the productivity and safety on construction sites. Site layout planning, however, is a complex problem, and researchers have attempted to solve it using a variety of optimization-based and heuristic-based techniques. In this paper, a genetic-algorithm-based model for site layout planning is presented. The advantages of the model stem from three main characteristics: (1) It applies to any user-defined site shape; (2) it accounts for the user preference in the relative closeness among the facilities; and (3) it incorporates a genetic algorithm procedure to search for the optimum layout in a manner that simulates natural evolution. Based on the proposed model, a comprehensive system for site layout planning (EvoSite) is developed. EvoSite uses an intuitive spreadsheet representation of the site and the facilities, and automates the evolution of layout solutions. Details of model development and implementation are described, and an example application is presented to demonstrate the capabilities of the EvoSite system. The advantages, limitations, and future extensions of EvoSite are then discussed.     

Review of Life-Cycle Assessment Applications in Building Construction

Life-cycle assessment (LCA) has been used to assess product development processes “from cradle to grave” for many years. With the current push toward sustainable construction, LCA has gained importance as an objective method to evaluate the environmental impact of construction practices. A substantial amount of construction-related LCA work has been published recently; however, most of this work has been fragmented and a systematic compilation of this literature has not been undertaken. This article presents a structured review of building construction-related LCA literature, classified under four categories: LCA applications for construction products selection; LCA applications for construction systems/process evaluation; LCA tools and databases related to the construction industry; and LCA methodological developments related to the construction industry. Current challenges for using LCA in construction are discussed and potential areas for future research are highlighted. This review and similar efforts may provide the construction industry and associated researchers the necessary background to make better-informed construction decisions and assist the development of an agenda for further research.     

Genetic Algorithm for Solving Site Layout Problem with Unequal-Size and Constrained Facilities

This paper presents an investigation of the applicability of a genetic approach for solving the construction site layout problem. This problem involves coordinating the use of limited site space to accommodate temporary facilities so that transportation cost of materials is minimized. The layout problem considered in this paper is characterized by affinity weights used to model transportation costs between facilities and by geometric constraints that limit their relative positions on site. The proposed genetic algorithm generates an initial population of layouts through a sequence of mutation operations and evolves the layouts of this population through a sequence of genetic operations aiming at finding an optimal layout. The paper concludes with examples illustrating the strength and limitations of the proposed algorithm in the cases of (1) loosely versus tightly constrained layouts with equal levels of interaction between facilities; (2) loosely versus tightly packed layouts with variable levels of interactions between facilities; and (3) loosely versus tightly constrained layouts. In most problems considered where the total-objects-to-site-area ratio did not exceed 60%, the algorithm returned close to optimal solutions in a reasonable time.     

Dynamic Layout Planning Using a Hybrid Incremental Solution Method

Efficiently using site space to accommodate resources throughout the duration of a construction project is a critical problem. It is termed the “dynamic layout planning” problem. Solving it involves creating a sequence of layouts that span the entire project duration, given resources, the timing of their presence on site, their changing demand for space over time, constraints on their location, and costs for their relocation. A dynamic layout construction procedure is presented here. Construction resources, represented as rectangles, are subjected to two-dimensional geometric constraints on relative locations. The objective is to allow site space to all resources so that no spatial conflicts arise, while keeping distance-based adjacency and relocation costs minimal. The solution is constructed stepwise for consecutive time frames. For each resource, selected heuristically one at a time, constraint satisfaction is used to compute sets of feasible positions. Subsequently, a linear program is solved to find the optimal position for each resource so as to minimize all costs. The resulting sequence of layouts is suboptimal in terms of the stated global objective, but the algorithm helps the layout planner explore better alternative solutions.