Journal of Construction Engineering and Management

Road tunnel construction is subject to underground uncertainties and risks, and as such it is difficult to predict the final construction cost, especially at the conception phase where issues are evaluated and important design decisions are made. A system assisting in the early cost estimation of road tunnels would therefore be of great value as it would allow the quick costing of alternative and more economical solutions. The development of such an early cost estimation system is discussed in this paper. First, the basic parameters (geological, geometrical, and work quantities-related) affecting temporary and permanent support and final construction cost are determined. After that, appropriate real-world data derived from the analysis of 33 twin tunnels of 46 km total length constructed for the Egnatia Motorway in northern Greece from 1998 to 2004 and related to work quantities is collected and normalized. Appropriate price lists are then applied to calculate the costs; subsequently, cost-estimating models are developed using two types of neural networks: (1) the multilayer feed-forward network; and (2) the general regression neural network. Finally, these models are compared against real quantities and costs for accuracy and robustness. The main conclusion is that the models developed are fit for their purpose and may lead to fairly accurate work quantities and cost estimates of road tunnels.

Project deadline and resource limits are practical constraints that coexist in most projects. While heuristic methods for constrained resource scheduling (CRS) have become mainstream in commercial scheduling software, no commercial software includes any time-cost trade-off (TCT) heuristic to help meet deadline, let alone any procedure to resolve both deadline and resource constraints. This paper, therefore, introduces a practical heuristic method to meet both deadline and resource limits. The proposed method basically uses cycles of crashing for lowest-cost critical activities (i.e., stepwise TCT process) and resolves any resource overallocation (i.e., CRS) within each TCT cycle. This intertwined approach is logical, fast, and provides a set of feasible project durations that do not violate resource limits. To facilitate its practical use, the proposed method has been programmed as an add-in tool to Microsoft Project software. The paper discusses several case studies that prove the practicality and usefulness of the proposed approach to both researchers and professionals and provides a comparison of results with other literature efforts.

Construction productivity improvement has become a key area of focus among academia and industry over the last decade attributable to its strong potential in benefitting the construction industry. Despite its high impact on the construction industry, productivity improvement is still an area in which much research work needs to be done to explore its true potential in a practical industry context. Today’s construction industry seems to adopt productivity improvement initiatives to gain a competitive edge in the global market place; however, systematization of these approaches is still an area of concern. This paper discusses a framework for the implementation of productivity improvement activities on a construction site, making the process more systematic, accountable, and sustainable with the creation of the construction productivity improvement officer (CPIO), a dedicated position, on construction sites.

Forecasting the supply of labor in the construction industry is pivotal to long-term economic growth. A labor supply model using a stock-flow approach was developed in this research for use in the construction industry. The model was tested using Hong Kong census statistics and data derived from interviews with 3,000 randomly selected construction workers. The findings were determined using a stock-flow model, which enabled the determination of future aging distribution trends and workforce supply for specific trade types. The developed stock-flow model can be effectively used in countries in which registration schemes for construction workers are in use.

A fast-track project delivery strategy is designed to leverage the ability to execute the design, procurement, and construction phases simultaneously to substantially reduce the overall project duration. The successful execution of the design phase in fast-track projects is especially challenging because the concurrent execution of design and construction interferes with the inherently iterative nature of the design process. In this research, it was hypothesized that a correlation exists between the use of some of the Construction Industry Institute (CII) best practices and the performance of design phase in fast-track projects. Analysis of the performance of the design phase in 31 fast-track projects revealed a statistically significant correlation between performance of the design phase and front-end planning, alignment, constructability, and change management. The results of quantitative analysis are supported by qualitative analysis of data, opinion of experts from industry, and academia. The projects analyzed in the study were executed by CII member companies with experience and knowledge of using the best practices effectively.

Oil prices may continue to rise indefinitely until alternative fossil fuels or renewable energies are commercialized. In this sense, general contractors who have the responsibility of delivering construction materials should select an optimized alternative that needs the least oil among the various combinations of truck types of logistic companies, routes, and suppliers. In this context, the objective of this paper was to develop a genetic-algorithm (GA)-based fuel-efficient transfer path selection model (GAFETPSM) for delivering construction materials with minimum fuel consumption. A GAFETPSM considers the truck type, road type, and fuel-efficiency variation by load, and the constraints of capacity, number of trucks, and total load to be delivered. Finally, a case study showed that GAFETPSM is superior to the simulated-annealing (SA)-based model in terms of fuel consumption in delivering the same weight of construction materials. It is expected that GAFETPSM could contribute to reduce the carbon-dioxide emission by using less oil.

Sustainability assessment tools are critical in the process of achieving sustainable development. Eco-efficiency has emerged as a practical concept that combines environmental and economic performance indicators to measure the sustainability performance of different product alternatives. In this paper, an analytical tool that can be used to assess the eco-efficiency of construction materials is developed. This tool evaluates the eco-efficiency of construction materials by using data envelopment analysis, a linear programming-based mathematical approach. Life-cycle assessment (LCA) and life-cycle cost (LCC) are utilized to derive the eco-efficiency ratios, and data envelopment analysis (DEA) is used to rank material alternatives. Developed mathematical models are assessed by selecting the most eco-efficient exterior wall finish for a building. Percent improvement analysis was carried out to investigate target environmental effect categories that need more reduction to reach 100% eco-efficiency. Through this study, the goal is to show that DEA-based eco-efficiency assessment model could be used to evaluate alternative construction materials and offer vital guidance for decision makers during material selection.

Existing literature has not provided conclusive performance results for green building energy efficiency. Existing studies produced debated conclusions and failed to represent a geographic concentration of structures from hot and dry climates. This technical paper examines 47% of Arizona’s 53 building Leadership in Energy and Environmental Design for New Construction (LEED NC) building population in an effort to determine if Arizona’s LEED NC buildings achieve expected energy performance, how they compare with the existing building population and whether either system or managerial variables demonstrate efficiency correlations. Data collection efforts were successful for all desired deliverables. Analysis of the LEED NC sample returned mixed results. On average, Arizona’s LEED NC medium energy intense (MEI) buildings performed better than the national average yet worse than buildings located in similar climates. Certain LEED NC MEI building types did demonstrate greater efficiencies than the corresponding Commercial Building Energy Consumption Survey population. Arizona’s high energy intense (HEI) structures performed considerably lower than national and similar climate averages. The LEED NC sample also underperformed both the design and baseline energy use simulations. Energy consumption correlation analysis returned very few statistically significant results. The study’s results demonstrate to industry practitioners and researchers that the LEED NC rating system’s energy strategies fail to meet modeled efficiencies, thereby highlighting a need for ongoing scrutiny and diligence when measuring sustainability and efficiency within Arizona’s built environment.

Contractors play a vital role in the overall performance of a project. Selecting the right contractor for the right project is the most crucial challenge for any construction client. Numerous and often conflicting objectives and alternatives, such as tender price, completion date, and experience, need to be considered. Recently, to assist owners in making decisions, there has been a trend away from a “lowest-price wins” principle and subjective judgement to a multicriteria selection approach in the selection of contractors for construction projects. In the autonomous region of Cantabria, in the north of Spain, increased project complexity and higher requirements have recently demanded the use of multicriteria decision-making methods for contractor selection. With this aim, two multicriteria decision methods, the technique for order preference by similarity to ideal solution (TOPSIS) and vlsekriterijumska optimizacija I kompromisno resenje (VIKOR) methods, are applied to the selection of a contractor for the road building project “La Braguía” undertaken during 2002. The results show that one of the contractors is the highest ranked by both methods. Being the highest ranked alternative by the TOPSIS method indicates that this contractor is the best in terms of the ranking index. In addition, being the highest ranked alternative by the VIKOR method indicates that it is the closest to the ideal solution.

This paper presents a method for project cost contingency forecasting and updating based on Value at Risk at a certain confidence level during project execution. The method is applied and demonstrated through an ongoing tunnel construction project lasting for several years. The method makes use of newly available information as the project progresses, and project daily cost and daily progress are analyzed and used as inputs for the quantitative model. The forecasts compare favorably with actual contingencies. The method provides opportunities to update contingencies at project milestones and to allocate appropriate contingencies at different project phases. This is beneficial for major companies which run multiple projects lasting for years, allowing them to set appropriate contingencies on certain timelines and to improve resource utilization.

For those construction companies engaged in projects where production is controlled by equipment availability, with tunneling as maybe the most extreme example, equipment replacement policies affect not just the cost of a machine but have a decisive effect on overall project cost and achieved profit. Although equipment replacement models described in the literature suggest that the consequential costs of equipment failure are significant and should be considered in replacement decisions, most fail to explicitly include consequential costs or fail to provide methods to calculate the consequential cost in complex systems. This lack of consequential cost in a model seriously diminishes the effectiveness of a company’s equipment replacement policies and the company’s ability to earn a project. This work describes a case study that used simulation to quantify the consequential costs of equipment availability for a company engaged in tunnel-construction. The study includes the simulation of activities of the drill-and-blast method for five tunnel types. The simulation proved to be very valuable when seeking to evaluate consequential costs. The results indicate that consequential costs are very relevant to the replacement decision of the most expensive equipment. Also, the results show a significant effect of the consequential costs on the company’s equipment replacement policies. Therefore, changes in existing policies to consider consequential costs have the potential of providing important future benefits for such companies.

Concrete precast plants require strict control over and adherence to the timing and sequence of operations. Variation for this research is divided into the variation in task starting time (the difference between the planned and the actual starting time) and the variation in task duration (the difference between the planned and the actual task duration). This study determined causes of variation in task starting time and duration of precast concrete slab production tasks. It also identified penalties associated with not reducing variation, which include an increase in project duration, Work in-Progress (WIP) and cost and a decrease in labor productivity. Additionally, two execution policies (keeping laborers waiting before preconditions are ready and keeping laborers busy) in the face of variation were compared by using STROBOSCOPE simulation techniques. It was found that simply keeping workers busy is insufficient for managing variation. Management effort should be devoted to eliminate causes of variation in the planning stage to make a reliable work plan. The results will help prefabricators to understand causes and penalties of variation, which is the starting point of attacking and reducing it. Although this study is based on a concrete slab production facility, this research can have a broader effect on the construction industry because the research method and simulation models developed in this study are applicable to other fabrication processes as well.