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.     

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.     

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.     

Optimal Schedule Planning for Multiple, Repetitive Construction Process

This study attempts to develop a construction scheduling model using a conceptual approach to improve the efficiency of construction resources for a multiple, repetitive construction process (MRCP). It is important for a project manager to arrange the number of horizontal repetitive work areas by each crew group to reduce the work interruption period in MRCP. This study suggests some equations for estimating the optimal number of horizontal repetitive work areas for a crew group and pursued a conceptual model for MRCP, which can reduce the loss in manpower and use of construction equipment that is caused by work interruption periods. A computer program developed for the analysis of MRCP shows an appropriate performance through the application to a case study based on the proposed procedure model in this study. Supposing that there is time to spare in the project completion date, the result of the study shows that cost loss could be greatly reduced by the proposed methodology.     

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.     

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.     

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.     

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.     

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.     

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.     

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.     

Efficient Hybrid Genetic Algorithm for Resource Leveling via Activity Splitting

Resource leveling problem is an attractive field of research in project management. Traditionally, a basic assumption of this problem is that network activities could not be split. However, in real-world projects, some activities can be interrupted and resumed in different time intervals but activity splitting involves some cost. The main contribution of this paper lies in developing a practical algorithm for resource leveling in large-scale projects. A novel hybrid genetic algorithm is proposed to tackle multiple resource-leveling problems allowing activity splitting. The proposed genetic algorithm is equipped with a novel local search heuristic and a repair mechanism. To evaluate the performance of the algorithm, we have generated and solved a new set of network instances containing up to 5,000 activities with multiple resources. For small instances, we have extended and solved an existing mixed integer programming model to provide a basis for comparison. Computational results demonstrate that, for large networks, the proposed algorithm improves the leveling criterion at least by 76% over the early schedule solutions. A case study on a tunnel construction project has also been examined.     

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.     

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.     

Multiproject Planning and Resource Controls for Facility Management

Facility managers face the challenges of managing many different types of small, geographically dispersed construction projects. Depending on the complexity and distribution of projects, the time required to prepare for production consumes a large percentage of the total time required to complete the job. Increasing crews’ productive hours is a key objective when planning multiproject schedules. Existing methods, however, lack the effective means to explicitly model, analyze, and optimize resource utilization for these multiple concurrent projects. As a result, few facility managers fully exploit the potential to better manage their often limited budget and resources. This paper presents an explicit model of the mobilization requirements of multiple crews performing a variety of different activities over a geographic space. The model allows the facility manager to explicitly investigate the impact of crew composition, crew specialization, and depot locations. Using work rule decisions regarding alternative crew allocations, facility managers may dynamically allocate resources to optimize resources and to complete projects in a minimum amount of time. To verify and validate this new model, a computerized system, called FIRS (Facility/Infrastructure Resource Scheduler), was created to analyze the multiproject resource plans with data from two military organizations and a university campus. FIRS utilizes a new genetic algorithm that was developed specifically to work with multiproject scheduling. Using FIRS, facility managers can develop and test alternative crew allocations based on the qualifications of the crews available and the type of operation being performed.     

Symbiotic Crew Relationships and Labor Flow

This paper introduces a concept heretofore unrecognized in multiple crew relationships: symbiotic crew relationships. A symbiotic relationship occurs when the work pace of one crew depends on the pace of a preceding crew. Data from steel reinforcement activities from six commercial and residential projects in Brazil are used to demonstrate the negative effects of symbiotic relationships. The steel reinforcement on the case study projects was cut and bent on site. In this context, the pace of the installation crew’s work (and hence performance) was dictated by the pace of the cutting and bending crew. The performance of crews with symbiotic relationships is shown to be consistently worse than when symbiotic relationships are not present. Symbiotic relationships are also tied to time buffers. There is better performance as the time buffer between crews approaches 5?days.     

Stochastic Modeling for Pavement Warranty Cost Estimation

This paper presents a cost estimation model for long-term pavement warranties with multiple distress indicators. One application area for such warranties involves performance-based specifications (PBSs). In contrast to traditional approaches, PBS gives contractors the flexibility to select construction methods, materials, and even design. However, the contractors then must warrant the performance of their work for a specified period of time. Therefore, an accurate estimation of the risks associated with the warranty is a significant cost issue for any contractor to cover potential risks while still being competitive in bidding. Quantitative evaluation of the cost of risk incurred by the warranty has several difficulties. The deterioration of a highway project is a complex process, which is affected by pavement structure, material, traffic load, and weather conditions. Based on a probabilistic risk analysis of failures of performance indicators, the resulting model can estimate the warranty cost at a detailed level. The application of the model has been demonstrated via a numerical case study using long-term pavement performance data.     

Optimal Strategy Modeling for Price-Time Biparameter Construction Bidding

In the price-time biparameter construction bidding system, each contractor submits a bid price and construction time to complete the project, which are then aggregated to a total combined bid (TCB) by the client, and the contractor with the lowest TCB is awarded the project. Since bid price can be set as construction cost plus an appropriate markup and construction cost usually depends on construction time, TCB can be expressed as a function of time. By minimizing such a TCB function, the optimal construction time can be obtained, from which the optimal construction cost and bid price and hence the optimal price-time bidding strategy can be sequentially decided. While examining the whole optimal bidding process, this paper focuses on three aspects to enhance the key ideas: discussing the properties of the general and the quadratic time-cost functions, deducing the optimal bidding formulas with quadratic time-cost relationship, and illustrating the procedures for estimating the quadratic time-cost function using a few experience data and the linear regression method. The in-depth examination of the price-time biparameter bidding model in the paper can suggest ideas and methodologies to construction bidding or contractor selection with more criteria.     

Method to Determine Minimum Contract Bid for A+B+I?/D Highway Projects

More and more state highway agencies (SHAs) have begun to consider the value of time in highway construction. The “A?(cost)+B?(time?cost)+I/D?(incentive/disincentive)” bidding concept is designed to shorten the total contract time by allowing each contractor to bid the number of days in which the work can be accomplished, in addition to the traditional cost bid. I/D are not only used to provide an incentive to the contractor for earlier completion, but also to provide a disincentive for late completion of a project. Contractors are then presented with the problem of determining the best strategy of bid estimation, including construction cost, time cost, and incentive/disincentive. SHAs are also faced with the problem of placing a maximum and/or minimum on the time bid. To provide users a useful tool to estimate project time more accurately using this advanced method, this study develops a quantified model of the price-time bidding contract. The functional relationship between the construction cost and time duration is developed based on data from the Florida Department of Transportation (FDOT). The contractor’s construction cost “A” is then combined with the road user cost and incentive/disincentive to determine the optimum low bid price and time. This optimum can then be used by the SHA to set limits on the range of acceptable time bids. Finally, several projects completed by the FDOT will be used to illustrate the validity of this 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.