Cost Optimization in Projects with Repetitive Nonserial Activities

A practical model for scheduling and cost optimization of repetitive projects is proposed in this paper. The model objective is to minimize total construction cost comprising direct cost, indirect cost, interruption cost, as well as incentives and liquidated damages. The novelty of this model stems from four main aspects: (1) it is based on full integration of the critical path and the line of balance methodologies, thus considering crew synchronization and work continuity among nonserial activities; (2) it performs time-cost trade-off analysis considering a specified deadline and alternative construction methods with associated time, cost, and crew options; (3) it is developed as a spreadsheet template that is transparent and easy to use; and (4) it utilizes a nontraditional optimization technique, genetic algorithms, to determine the optimum combination of construction methods, number of crews, and interruptions for each repetitive activity. To automate the model, macroprograms were developed to integrate it with commercial scheduling software. Details of the model are presented, and an example project is used to demonstrate its benefits.     

Optimal Planning and Scheduling for Repetitive Construction Projects

This paper presents a multiobjective optimization model for the planning and scheduling of repetitive construction projects. The model enables construction planners to generate and evaluate optimal construction plans that minimize project duration and maximize crew work continuity, simultaneously. The computations in the present model are organized in three major modules: scheduling, optimization, and ranking modules. First, the scheduling module uses a resource-driven scheduling algorithm to develop practical schedules for repetitive construction projects. Second, the optimization module utilizes multiobjective genetic algorithms to search for and identify feasible construction plans that establish optimal tradeoffs between project duration and crew work continuity. Third, the ranking module uses multiattribute utility theory to rank the generated plans in order to facilitate the selection and execution of the best overall plan for the project being considered. An application example is analyzed to illustrate the use of the model demonstrate its new capabilities in optimizing the planning and scheduling of repetitive construction projects.     

Application of Support Vector Machines in Assessing Conceptual Cost Estimates

Total conceptual cost estimates and the assessment of the quality of these estimates are critical in the early stages of a building construction project. In this study, the support vector machine (SVM) model for assessing the quality of conceptual cost estimates is proposed, and the application of SVM in construction areas is investigated. The results show that the SVM model assessed the quality of conceptual cost estimates slightly more accurately than the discriminant analysis model. This shows that using the SVM has potential in construction areas. In addition, the SVM model can assist clients in their evaluation of the quality of the estimated cost and the probability of exceeding the target cost, and in their decision on whether or not it is necessary to seek a more accurate estimate in the early stages of a project.     

Optimizing Resource Utilization for Repetitive Construction Projects

Optimizing resource utilization can lead to significant reduction in the duration and cost of repetitive construction projects such as highways, high-rise buildings, and housing projects. This can be achieved by identifying an optimum crew size and interruption strategy for each activity in the project. Available dynamic programming formulations can be applied to provide solutions for this optimization problem; however, their application is limited, as they require planners to specify an arbitrary and an unbounded set of interruption options prior to scheduling. Such a requirement is not practical and may render the optimization problem infeasible. To circumvent the limitations of available formulations, this paper presents an automated and practical optimization model. The model utilizes dynamic programming formulation and incorporates a scheduling algorithm and an interruption algorithm so as to automate the generation of interruptions during scheduling. This transforms the consideration of interruption options, in optimizing resource utilization, from an unbounded and impractical problem to a bounded and feasible one. A numerical example from the literature is analyzed to illustrate the use and capabilities of the model.     

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.     

Object-Oriented Model for Repetitive Construction Scheduling

This paper presents the development of an object-oriented model for scheduling of repetitive construction projects such as high-rise buildings, housing projects, highways, pipeline networks, bridges, tunnels, railways, airport runways, and water and sewer mains. The paper provides an overview of the analysis, design, and implementation stages of the developed object-oriented model. These stages are designed to provide an effective model for scheduling repetitive construction projects and to satisfy practical scheduling requirements. The model incorporates newly developed procedures for resource-driven scheduling of repetitive activities, optimization of repetitive construction scheduling, and integration of repetitive and nonrepetitive scheduling techniques. The model is named LSCHEDULER and is implemented as a windows application that supports user-friendly interface including menus, dialogue boxes, and windows. LSCHEDULER can be applied to perform regular scheduling as well as optimized scheduling. In optimized scheduling, the model can assist in identifying an optimum crew utilization option for each repetitive activity in the project that provides a minimum duration or cost for the scheduled repetitive construction project.     

Sequence Planning for Electrical Construction

The sequences in which work is completed bear significantly on the performance of electrical contractors in building construction projects. When project work sequences are poorly planned or poorly executed, electrician constructors often must contend with compressed schedules, trade stacking, and out-of-sequence work to ensure timely completion of a project. This paper analytically evaluates the importance of sequence planning to efficient electrical work. It describes changes that were made to crew-level planning procedures for an electrical contractor and the impact these had on crew performance. The analysis shows that sequence planning at both the project level and the crew level are important to the performance of electrical crews. Most notably, a strong correlation (0.73) was detected between crew planning performance one week and crew productivity performance in the following week. Results of the study are provided. Principles of sound sequences and guidelines for sequence planning are also captured from the analysis. These sequence guidelines are designed to avoid, where possible, the often adverse project conditions in which electrical contractors find themselves and to handle those conditions most effectively when they cannot be avoided.     

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.     

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.     

Site Management of Work-in-Process Buffers to Enhance Project Performance Using the Reliable Commitment Model: Case Study

Buffers have been commonly used as a production strategy to protect construction processes from the negative impact of variability. Construction practitioners and researchers have proposed several buffering approaches for different production situations and contexts. However, these solutions have been impractical for managing buffers. To overcome this, this study proposes a new site methodology for managing work-in-process (WIP) buffer in repetitive projects, on the basis of the reliable commitment model (RCM). RCM is a decision-making tool based on lean principles, which uses statistical models to develop more reliable work plans at the operational level. RCM helps to manage WIP buffer in work plans by using site information and planning reliability indicators that result in improved project performance, such as labor productivity and process progress. A repetitive building project was used as a case study. The main finding was that labor productivity, process progress, and waiting times improved when using larger WIP buffers than those typically used among crews. This shows the potential of RCM as a practical tool to manage WIP buffer sizes and to promote the use of lean production strategies at the operational level.     

Parade Game: Impact of Work Flow Variability on Trade Performance

The Parade Game illustrates the impact work flow variability has on the performance of construction trades and their successors. The game consists of simulating a construction process in which resources produced by one trade are prerequisite to work performed by the next trade. Production-level detail, describing resources being passed from one trade to the next, illustrates that throughput will be reduced, project completion delayed, and waste increased by variations in flow. The game shows that it is possible to reduce waste and shorten project duration by reducing the variability in work flow between trades. Basic production management concepts are thus applied to construction management. They highlight two shortcomings of using the critical-path method for field-level planning: The critical-path method makes modeling the dependence of ongoing activities between trades or with operations unwieldy and it does not explicitly represent variability. The Parade Game can be played in a classroom setting either by hand or using a computer. Computer simulation enables students to experiment with numerous alternatives to sharpen their intuition regarding variability, process throughput, buffers, productivity, and crew sizing. Managers interested in schedule compression will benefit from understanding work flow variability's impact on succeeding trade performance.     

Efficient Repetitive Scheduling for High-Rise Construction

A new scheduling and cost optimization model for high-rise construction is presented in this paper. The model has been formulated with a unique representation of the activities that form the building’s structural core, which need to be dealt with carefully to avoid scheduling errors. In addition, the model has been formulated incorporating: (1) the logical relationships within each floor and among floors of varying sizes; (2) work continuity and crew synchronization; (3) optional estimates and seasonal productivity factors; (4) prespecified deadline, work interruptions, and resource constraints; and (5) a genetic algorithms-based cost optimization that determines the combination of construction methods, number of crews, and work interruptions that meet schedule constraints. A computer prototype was then developed to demonstrate the model’s usefulness on a case study high-rise project. The model is useful to both researchers and practitioners as it better suits the environment of high-rise construction, avoids scheduling errors, optimizes cost, and provides a legible presentation of resource assignments and progress data.     

Scheduling∕Cost Optimization and Neural Dynamics Model for Construction

A general mathematical formulation is presented for the scheduling of construction projects and is applied to the problem of highway construction scheduling. Repetitive and nonrepetitive tasks, work continuity constraints, multiple-crew strategies, and the effects of varying job conditions on the performance of a crew can be modeled. An optimization formulation is presented for the construction project scheduling problem, with the goal of minimizing the direct construction cost. The nonlinear optimization is then solved by the neural dynamics model developed recently by Adeli and Park. For any given construction duration, the model yields the optimum construction schedule for minimum construction cost automatically. By varying the construction duration, one can solve the cost-duration trade-off problem and obtain the global optimum schedule and the corresponding minimum construction cost. The new construction scheduling model provides the capabilities of both the critical path method (CPM) and linear scheduling method (LSM) approaches. In addition, it provides features desirable for repetitive projects, such as highway construction, and allows schedulers greater flexibility. It is particularly suitable for studying the effects of change order on the construction cost. This research provides the mathematical foundation for development of a new generation of more general, flexible, and accurate construction scheduling systems.     

Model for Predicting the Performance of Project Managers at the Construction Phase of Mass House Building Projects

The need to match project managers’ (PMs) performance measures onto projects of both unique and similar characteristics has long since been acknowledged by researchers. The need for these measures to reflect the various phases of the project life cycle has also been contended in the recent past. Here, a competency-based multidimensional conceptual model is proposed for mass house building projects (MHBPs). The model reflects both performance behaviors and outcome in predicting the PMs’ performances at the conceptual, planning, design, tender, construction, and operational phases of the project life cycle. Adopting a positivist approach, data elicited for the construction phase is analyzed using multiple regression techniques (stepwise selection). Out of a broad range of behavioral metrics identified as the independent variables, the findings suggest the best predictors of PMs’ performances in MHBPs at the construction phase are: job knowledge in site layout techniques for repetitive construction works; dedication in helping works contractors achieve works schedule; job knowledge of appropriate technology transfer for repetitive construction works; effective time management practices on house units; ability to provide effective solution to conflicts, simultaneously maintaining good relationships; ease with which works contractors are able to approach the PM and volunteering to help works contractors solve personal problems. ANOVA, multicollineriality, Durbin–Watson, and residual analysis, confirm the goodness of fit. Validation of the model also reflected reasonably high predictive accuracy suggesting the findings could be generalized. These results indicate that the model can be a reliable tool for predicting the performance of PMs in MHBPs.     

Integrated Schedule and Cost Model for Repetitive Construction Process

Several efforts have been made by many researchers to develop a model for schedule and cost integration in construction projects, but it is difficult to integrate and manage schedule and cost in an actual construction site using such a model. The integrated schedule and cost model developed in this study (1) enables the planning and control of repetitive construction processes and (2) can be used by a project manager in an actual construction site. Furthermore, an integrated schedule and cost model for the core wall construction, which is an important repetitive process in the recently booming high-rise building construction in terms of scheduling, was developed using the integration model developed in this study. It is expected that the integrated schedule and cost model developed can allow project managers to integrate the schedule and cost of repetitive construction processes more effectively and support the project managers’ decision-making.     

Strategic-Operational Construction Management: Hybrid System Dynamics and Discrete Event Approach

A significant number of large-scale civil infrastructure projects experience cost overruns and schedule delays. To minimize these disastrous consequences, management actions need to be carefully examined at both the strategic and operational levels, as their effectiveness is mainly dependent on how well strategic perspectives and operational details of a project are balanced. However, current construction project management approaches have treated the strategic and operational issues separately, and consequently introduced a potential conflict between strategic and operational analyses. To address this issue, a hybrid simulation model is presented in this paper. This hybrid model combines system dynamics and discrete event simulation which have mainly been utilized to analyze the strategic and operational issues in isolation, respectively. As an application example, a nontypical repetitive earthmoving process is selected and simulated. The simulation results demonstrate that a systematic integration of strategic perspective and operational details is helpful to enhance the process performance by enabling construction managers to identify potential process improvement areas that traditional approaches may miss. Based on the simulation results, it is concluded that the proposed hybrid simulation model has great potential to support both the strategic and operational aspects of construction project management and to ultimately help increase project performance.     

Siren: A Repetitive Construction Simulation Model

SIREN (SImulation of REpetitive Networks) is a computer model of repetitive construction such as the construction of multi‐story buildings, housing estates, linear projects, etc. The user interactively inputs a precedence diagram for the repetitive unit (e.g., one floor of a skyscraper) and additional “sub‐networks” that are not part of the repetitive sequence (e.g., first floor of skyscraper). From this information, the computer generates the whole network. Data is input via an IBM‐PC at which point extensive error checking is carried out. The model itself is coded in the GPSS language and runs on a remote mainframe computer. It simulates the various crews as they queue to carry out activities. A working schedule and cumulative cost curve are produced and statistics are gathered on crew and equipment utilization, all being output graphically. A Monte‐Carlo simulation is also included as probability distributions may be associated with the duration of each activity. This yields confidence intervals on cumulative costs throughout the project and on milestone attainment.     

Development of Causal Model of Construction Accident Causation

Accidents occur in all types of construction activities. The accident causation process is complex. Accident prevention requires a comprehensive understanding of this complex process. This paper proposes a conceptual, but practical, model of accident causation for the construction industry, highlighting the underlying and complex interaction of factors in the causation process. The model describes the constraints and responses experienced by the parties involved in project conception, design, and construction, which may affect accident causation. This paper details theoretical findings of research currently being conducted at UMIST. Both proximal and distal factors are considered (for example, operative factors, site environment and systems of work, and project management and organizational issues). A study of 500 accident records provided by the U.K. Health and Safety Executive shows that accidents in construction projects involve inappropriate construction planning (28.8%), inappropriate construction control (16.6%), inappropriate construction operation (88.0%), inappropriate site condition (6.0%), and inappropriate operative action (29.9%). Data currently available are, in some respects, inadequate and will need to be supplemented, in the future, by extended accident investigations.     

Multiobjective Linear Programming Model for Scheduling Linear Repetitive Projects

Linear repetitive construction projects require large amounts of resources which are used in a sequential manner and therefore effective resource management is very important both in terms of project cost and duration. Existing methodologies such as the critical path method and the repetitive scheduling method optimize the schedule with respect to a single factor, to achieve minimum duration or minimize resource work breaks, respectively. However real life scheduling decisions are more complicated and project managers must make decisions that address the various cost elements in a holistic way. To respond to this need, new methodologies that can be applied through the use of decision support systems should be developed. This paper introduces a multiobjective linear programming model for scheduling linear repetitive projects, which takes into consideration cost elements regarding the project’s duration, the idle time of resources, and the delivery time of the project’s units. The proposed model can be used to generate alternative schedules based on the relative magnitude and importance of the different cost elements. In this sense, it provides managers with the capability to consider alternative schedules besides those defined by minimum duration or maximizing work continuity of resources. The application of the model to a well known example in the literature demonstrates its use in providing explicatory analysis of the results.     

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.