Application Example for Evaluating Networks Considering Correlation

Current approaches to network scheduling do not consider the correlation between activity durations. When activity durations are correlated, the variability of path and project durations may be increased. High variability in a project's duration increases the uncertainty of completing the project by a target date. The model NETCOR (NETworks under CORrelated uncertainty) has been developed to evaluate schedule networks when activity durations are correlated. The NETCOR model builds upon a factor-based procedure to indirectly elicit correlation. An activity duration model disaggregates the effect of uncertainty by factors from a duration distribution (grandparent) for each activity. Correlation is captured by a child-distribution approach that further breaks down the factor-subdistribution (parent) based on the factor conditions. This paper demonstrates the practical application of NETCOR to a current construction project. Using the same inputs, the program evaluation and review technique and several simulation analyses that do not consider correlation also are evaluated. Comparison of the results shows the significance of considering correlation in scheduling analysis.     

Construction Project Network Evaluation with Correlated Schedule Risk Analysis Model

Schedules are the means of determining project duration accurately, controlling project progress, and allocating resources efficiently in managing construction projects. It is not sufficient in today’s conditions to evaluate the construction schedules that are affected widely by risks, uncertainties, unexpected situations, deviations, and surprises with well-known deterministic or probabilistic methods such as the critical path method, bar chart (Gantt chart), line of balance, or program evaluation and review technique. In this regard, this paper presents a new simulation-based model—the correlated schedule risk analysis model (CSRAM)—to evaluate construction activity networks under uncertainty when activity durations and risk factors are correlated. An example of a CSRAM application to a single-story house project is presented in the paper. The findings of this application show that CSRAM operates well and produces realistic results in capturing correlation indirectly between activity durations and risk factors regarding the extent of uncertainty inherent in the schedule.     

Model for Evaluating Networks under Correlated Uncertainty—NETCOR

Construction activities are often influenced by factors such as weather, labor, and site conditions. When several activities are influenced by the same factor, their durations may be correlated. If many activities along a path are correlated, the variability of path duration will increase, possibly increasing the uncertainty of completing the project by a target date. This paper presents the simulation-based model NETCOR (NETworks under CORrelated uncertainty) to evaluate schedule networks when activity durations are correlated. Based on qualitative estimates of the sensitivity of each activity to each factor, uncertainty in an activity's duration distribution (grandparent) is distributed to several factor subdistributions (parents). Each subdistribution is broken down further into a family of distributions (children), with each child corresponding to a factor condition. Correlation is captured by sampling from the same-condition child distributions for a given iteration of the simulation. NETCOR integrates the effect due to each factor at the path level. Awareness of the factors to which a path is sensitive can provide management with a better sense of what to control on each path, particularly on large projects.     

Project Planning for Construction under Uncertainty with Limited Resources

Much of the project scheduling literature treats task durations as deterministic. In reality, however, task durations are subject to considerable uncertainty, and that uncertainty can be influenced by the resources assigned. The purpose of this paper is to provide the means for contractors to optimally allocate their skilled workers among individual tasks for a single project. Instead of the traditional use of schedules, we develop control policies in the form of planned resource allocation to tasks that capture the uncertainty associated with task durations and the impact of resource allocation on those durations. We develop a solution procedure for the model and illustrate the ideas in an example. The data for the example is collected from a real project.     

Fuzzy Logic Approach for Activity Delay Analysis and Schedule Updating

This paper presents a fuzzy logic model that integrates daily site reporting of activity progress and delays, with a schedule updating and forecasting system for construction project monitoring and control. The model developed assists in the analysis of the effects of delays on a project’s completion date and consists of several components: An as-built database integrated with project scheduling; a list of potential causes for delays; a procedure to categorize delays; a method of estimating delay durations utilizing fuzzy logic; a procedure that updates the schedule; and, a procedure that evaluates the effects and likely consequences of delays on activity progress. This model is of relevance to researchers since it makes a contribution in project scheduling by developing a complete approach for handling the uncertainty inherent in schedule updating and activity delay analysis. It also advances the application of fuzzy logic in construction. It is of relevance to construction industry practitioners since it provides them with a useful technique for incorporating as-built data into the schedule, assessing the impact of delays on the schedule, and updating the schedule to reflect the consequences of delays and corrective actions taken. The use of fuzzy logic in the model allows linguistic and subjective assessments to be made, and thereby suits the actual practices commonly used in industry.     

Hybrid Time-Cost Optimization of Nonserial Repetitive Construction Projects

Time-cost trade-off analysis represents a challenging task because the activity duration and cost have uncertainty associated with them, which should be considered when performing schedule optimization. This study proposes a hybrid technique that combines genetic algorithms (GAs) with dynamic programming to solve construction projects time-cost trade-off problems under uncertainty. The technique is formulated to apply to project schedules with repetitive nonserial subprojects that are common in the construction industry such as multiunit housing projects and retail network development projects. A generalized mathematical model is derived to account for factors affecting cost and duration relationships at both the activity and project levels. First, a genetic algorithm is utilized to find optimum and near optimum solutions from the complicated hyperplane formed by the coding system. Then, a dynamic programming procedure is utilized to search the vicinity of each of the near optima found by the GA, and converges on the global optima. The entire optimization process is conducted using a custom developed computer code. The validation and implementation of the proposed techniques is done over three axes. Mathematical correctness is validated through function optimization of test functions with known optima. Applicability to scheduling problems is validated through optimization of a 14 activity miniproject found in the literature for results comparison. Finally implementation to a case study is done over a gas station development program to produce optimum schedules and corresponding trade-off curves. Results show that genetic algorithms can be integrated with dynamic programming techniques to provide an effective means of solving for optimal project schedules in an enhanced realistic approach.     

Probabilistic Duration Estimation Model for High-Rise Structural Work

The duration of a construction project is a key factor to consider before starting a new project, as it can determine project success or failure. Despite the high level of uncertainty and risk involved in construction, current construction planning relies on traditional deterministic scheduling methods that cannot clearly ascertain the level of uncertainty involved in a project. This, subsequently, can prolong a project’s duration, particularly when that project is high-rise structural work, which is not yet a common project type in Korea. Indeed, among construction processes, structural work is notable, as it is basically performed outdoors. Thus, no matter how precisely a schedule is developed, such projects can easily fail due to unexpected events that are beyond the planner’s control, such as changes in weather conditions. Therefore, in this study, to cope with the uncertainties involved in high-rise building projects, a probabilistic duration estimation model is developed in which both weather conditions and work cycle time for unit work are considered to predict structural work duration. According to the proposed estimation model, weather variables are divided into two types: weather conditions that result in nonworking days and weather conditions that result in work productivity rate (WPR) change. Obtained from actual previous data, the WPR is used with relevant nonworking day weather conditions to modify the actual number of working days per calendar days. Furthermore, on the basis of previous research results, the cycle time of the unit work area is assumed to follow the β probability distribution function. Thus, the probabilistic duration model is valid for 95% probability. Finally, a case study is conducted that confirms the model can be practically used to estimate more reliable and applicable probabilistic durations of structural work. Indeed, this model can assist schedulers and site workers by alerting them, at the beginning of a project, to project uncertainties that specifically pertain to structural work and the weather. Thus, the proposed model can enable personnel to easily amend, and increase the reliability of, the construction schedule at hand.     

Probabilistic Estimation and Allocation of Project Time Contingency

Project managers implement the concept of time contingency to consider uncertainty in duration estimates and prevent project completion delays. Some project managers also build a distribution of the project time contingency into the project activities to create a more manageable schedule. Generally, both the estimation and distribution of the project time contingency are conducted by using subjective approaches. Because the project schedule feasibility mainly depends on the variable behavior of the project activities, the estimate of project time contingency and its allocation at the activity level should be obtained by considering the performance variability of each activity rather than basing on human judgment. In this paper, the stochastic allocation of project allowances method, which is based on Monte?Carlo simulation, is proposed to estimate the project time contingency and allocate it among the project activities. The application of this method to a three-span bridge project results in a fair allocation of the project time contingency and provides practical means to control time contingencies at the activity level.     

Linear Scheduling Model with Varying Production Rates

Activity production rates drive the development and accuracy of linear schedules. The nature of linear projects dictates an assortment of variables that affect each activity’s production rate. The purpose of this research was to expand the capabilities of linear scheduling to account for variance in production rates when and where the variance occurs and to enhance the visual capabilities of linear scheduling. This new linear scheduling model, a linear scheduling model with varying production rates (LSMVPR), has two objectives. The first is to outline a framework to apply changes in production rates when and where they occur along the horizontal alignment of the project. The second objective is to illustrate the difficulty or ease of construction through the time-location chart. This research showed that the changes in production rates because of time and location can be modeled for use in predicting future construction projects. Using the concept of working windows, LSMVPR allows the scheduler to develop schedule durations on the basis of minimal project information. The model also allows the scheduler to analyze the impact of various routes or start dates for construction and the corresponding impact on the schedule. The graphical format allows the construction team to visualize the obstacles in the project when and where they occur by using a new feature called the activity performance index (API). This index is used to shade the linear scheduling chart by time and location with the variation in color indicating the variance in predicted production rate from the desired production rate.     

Application of Innovative Critical Chain Method for Project Planning and Control under Resource Constraints and Uncertainty

This research proposes an innovative critical chain method (ICCM) for project planning and control under resource constraints and uncertainty. An improved genetic algorithm is developed to identify the critical chain and to obtain the optimal start time of each activity under the most optimistic duration of each activity and resource constraints. Furthermore, a feeding buffer is added in an insert point in order to deal with uncertainties. The benefits of applying this ICCM are demonstrated in an example project.     

Optimized Scheduling of Linear Projects

This paper presents a model, designed to optimize scheduling of linear projects. The model employs a two-state-variable, N-stage, dynamic programming formulation, coupled with a set of heuristic rules. The model is resource-driven, and incorporates both repetitive and nonrepetitive activities in the optimization process to generate practical and near-optimal schedules. The model optimizes either project construction duration, total cost, or their combined impact for what is known as cost-plus-time bidding, also referred to as A+B bidding. The model has a number of interesting and practical features. It supports multiple crews to work simultaneously on any activity, while accounting for: (1) multiple successors and predecessors with specified lead and lag times; (2) the impact of transverse obstructions, such as rivers and creeks, on crew assignments and associated time and cost; (3) the effect of inclement weather and learning curve on crew productivity; and (4) variations in quantities of work in repetitive activities from one unit to another. The model is implemented in a prototype software that operates in Windows? environment. It is developed utilizing object-oriented programming, and provides for automated data entry. Several graphical and tabular output reports can be generated. An example project, drawn from the literature, is analyzed to demonstrate the features of the developed model.     

Methodology for Integrated Risk Management and Proactive Scheduling of Construction Projects

An integrated methodology is developed for planning construction projects under uncertainty. The methodology relies on a computer supported risk management system that allows for the identification, analysis, and quantification of the major risk factors and the derivation of their probability of occurrence and their impact on the duration of the project activities. Using project management estimates of the marginal cost of activity starting time disruptions, a heuristic procedure is used to develop a stable proactive baseline schedule that is sufficiently protected against the anticipated disruptions that may occur during project execution and that exhibits acceptable makespan performance. We illustrate the application of the methodology on a real life construction project and demonstrate that our proactive scheduler generates baseline schedules that outperform the schedules generated by commercial software packages in terms of robustness and timely project completion probability.     

Critical Path Segments Scheduling Technique

While the critical path method (CPM) has been useful for scheduling construction projects, years of practice and research have highlighted serious drawbacks that hinder its use as a decision support tool. This paper argues that many of CPM drawbacks stem from the rough level of detail at which the analysis is conducted, where activities’ durations are considered as continuous blocks of time. The paper thus proposes a new critical path segments (CPS) mechanism with a finer level of granularity by decomposing the duration of each activity into separate time segments. Three cases are used to prove the benefits of using separate time segments in avoiding complex network relationships, accurately identifying all critical path fluctuation, better allocation of limited resources, avoiding multiple-calendar problems, and accurate analysis of project delays. The paper discusses the proposed CPS mechanism and comments on several issues related to its calculation complexity, its impact on existing procedures, and future extensions. This research is more beneficial to researchers and has the potential to revolutionize scheduling computations to resolve CPM drawbacks.     

Reliability Buffering for Construction Projects

Buffering is a common practice in project planning. Project managers or schedulers have used a time contingency to guarantee the completion time of either an activity or a project. This traditional buffering, however, often fails to protect the project schedule performance, resulting in an unnecessary resource idle time. To deal with this problem, reliability buffering, a simulation-based buffering strategy, is presented. Reliability buffering aims to generate a robust construction plan that protects against uncertainties by reducing the potential impact of construction changes. The effectiveness of reliability buffering is examined by simulating a dynamic project model that integrates the simulation approach with the network scheduling approach. The research results indicate that reliability buffering can help achieve a shorter project duration without driving up costs by pooling, resizing, relocating, and recharacterizing contingency buffers. A case study of bridge construction projects also demonstrates how construction projects can benefit from reliability buffering in real world settings. Although further validation is needed, reliability buffering can potentially impact the planning and control of construction projects by improving the consideration of construction feedbacks and characteristics in buffering, and serving as an input to a dynamic project model.     

Optimum Planning of Highway Construction under A + B Bidding Method

In recent years, many departments of transportation in the United States have started to apply the A + B bidding method in highway projects in order to reduce construction time and minimize its associated traffic congestion and adverse impact on local economies. The application of this method places an increased pressure on contractors to minimize both the time and cost of highway construction. This paper presents a practical model for optimizing resource utilization in highway projects that utilize the A + B bidding method. The model is designed to minimize the total combined bid by identifying the optimum crew formation and the optimum level of crew work continuity for each activity in the project. The model is developed using a dynamic programming formulation and is incorporated in a Windows application that provides a user-friendly interface to facilitate the optimization analysis. An application example of a highway project is analyzed to illustrate the use of the model and to demonstrate its capabilities.     

Impact of Change Orders on Small Labor-Intensive Projects

In today’s construction, small projects can be just as important if not more important than the larger projects. However, small projects are usually fast track projects, which often involve overlapping design and construction time. Subsequent modifications may be required for the sections that are already under construction. These disruptions to the ongoing project are labeled as change orders. The impact due to changes has been described as the adverse effect upon the unchanged work due to changes in the contract. For this study, 34 projects were selected to develop a statistical model that estimates the amount of labor efficiency lost due to change orders for small projects. The variables in the final model are percent design related changes, percent owner initiated changes, the ratio of actual peak labor to estimated peak labor, the ratio of actual project duration to estimated project duration, and project manager’s percent time on the project. The results of this paper are of value to owners, electrical and mechanical contractors, and construction managers. The model quantifies the impact of change orders by introducing the most important variables that bring the largest disruptions.     

Work-Time Model for Engineers

The purpose of this paper is to present a work-time model for engineers. Engineers accomplish tasks by using their time when working on engineering or construction projects. Traditional project management records only work hours on tasks charged by engineers, but whether engineers spend time on direct work or communication is usually not tracked. Project tasks entail various degrees of uncertainty and ambiguity that require different work mechanisms and amounts of time. To address this issue, a model of arranging engineers' work mechanisms and time on tasks was developed. The model tested valid on a design project by showing that the fit between planned and actual work hour patterns is associated with better performance. From a system viewpoint, engineers' work mechanisms and time as input variables provide early symptomatic data and prediction about project operations, which provides a guide for the behavior of engineers.     

Improvement Algorithm for Limited Space Scheduling

Selecting construction methods, scheduling activities, and planning the use of site space are key to constructing a project efficiently. Site layout and activity scheduling have been tackled as independent problems. Their interdependence is often ignored at the planning stage and may be dealt with—if at all—when construction is underway. Problems that may have had easy solutions if dealt with earlier, may then be expensive to remedy. This paper addresses the combined problem termed “space scheduling” and presents an algorithmic time-space trade-off model for adjusting activity durations and start dates to decrease the need for space over congested time periods. The model characterizes resource space requirements over time and establishes a time-space relationship for each activity in the schedule, based on alternative resource levels. An example illustrates the presented algorithm that generates a feasible space schedule.     

Quantified dermal activity data from a four-child pilot field study

Thirty-three hours of videotape collected in a 1993 pilot study were quantified, via a video translation software application, to obtain left and right hand activity data of four children of farmworkers. Reported here are the children's contact duration and frequency for each object in their environment, duration spent in each location and activity exertion level, and frequency distributions of object contact durations. The pilot study provided valuable information for evaluating and improving videotaping and videotape translation methodologies as a means of gathering activity information that can be used to refine dermal exposure estimates. Although a larger database of children's videotaped activities for different ages and populations is needed before generalizations can be made, the data presented here are the most detailed information to date for children's micro-level dermal activities.     

Ordinal properties of perceived average duration: Simultaneous and sequential presentations.

When an S evaluates the duration of 2 simultaneous events, the perceived durations are combined in a nonlinear manner, whereas comparable evaluations of successive events yield linear combinations. In the present study, 54 undergraduates rated average durations of pairs of time intervals ranging from 0.5 to 10.0 sec. The intervals making up a pair were presented successively and simultaneously on separate occasions within the same presentation sequence. The order of data was consistent with models previously proposed for perceived average duration. A nonmetric analysis of the combined ordinal data from both conditions yielded a single set of measures of perceived duration with ratio-scale properties. The common scale for the 2 conditions is consistent with differences in results from simultaneous and successive monitoring of time intervals, stemming from differences in the way duration information is combined rather than how it is perceived. The derived scale is related to physical time by a power function with a 1.06 exponent. (19 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)