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.     

Fuzzy Repetitive Scheduling Method for Projects with Repeating Activities

In projects with repeating activities (such as multistory buildings, highways, or pipelines consisting of reiterating identical or similar units) and in which the activity unit production rates are characterized by uncertainty or imprecision, fuzzy set theory and the well-established repetitive scheduling method (RSM) can be combined to ensure uninterrupted usage of resources between similar activities in different units. The reason for this approach is that in practice the application of RSM may be hindered by several considerations, for example, repetitive units may be slightly different from each other, the performance of construction crews may vary, and there may be complex resource matching and sharing between activities and work sites. The proposed methodology is termed fuzzy repetitive scheduling method (F-RSM), and it requires a generalization of RSM in which schedules are represented by two- or three-dimensional graphs and whereby the concepts of a control segment and the controlling sequence area are introduced. The resulting methodology addressing the original RSM scheduling problem is presented in this paper.     

Object-Oriented Scheduling for Repetitive Projects with Soft Logics

The application of network techniques of project scheduling to repetitive projects has been criticized for the inability of network techniques to help maintain work continuity. Moreover, current network techniques require a large number of activities to represent a repetitive project and presume that there is only one logical sequence. This makes schedules time consuming to develop as well as maintain. Further, the logic chosen by the planner might be far from the shortest possible duration. This paper, utilizing the soft logic sequencing principles developed by Fan et al., develops a system which provides an easy input module in addition to scheduling and work-continuity-maintenance modules. The system eases the network generation and update processes, which in turn provides the shortest possible duration logics and the start and finish dates required to maintain work continuity.     

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.     

Non-Unit-Based Planning and Scheduling of Repetitive Construction Projects

Repetitive scheduling methods are more effective than traditional critical path methods in the planning and scheduling of repetitive construction projects. Nevertheless, almost all the repetitive scheduling methods developed so far have been based on the premise that a repetitive project is comprised of many identical production units. In this research a non-unit-based algorithm for the planning and scheduling of repetitive projects is developed. Instead of repetitive production units, repetitive or similar activity groups are identified and employed for scheduling. The algorithm takes into consideration: (1) the logical relationship of activity groups in a repetitive project; (2) the usage of various resource crews in an activity group; (3) the maintaining of resource continuity; and (4) the time and cost for the routing of resource crews. A sample case study and a case study of a sewer system project are conducted to validate the algorithm, as well as to demonstrate its application. Results and findings are reported.     

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.     

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.     

浅议工程项目成本管理

分析项目成本管理中存在的诸多问题及其原因，提出加强项目成本管理的措施。     

Modeling Cost Escalation in Large Infrastructure Projects

Cost overruns in large infrastructure projects have been commonplace in the past decades. Budgeting for cost escalation is a major issue in the planning phase of these projects. In this paper, we first review various methods of forecasting escalation factor and study the changes in construction costs in the past 25 years by analyzing movements of a cost index. We then introduce a system for modeling the escalation uncertainty in large multiyear construction projects. The system uses a Monte Carlo simulation approach and considers variability of project component durations and the uncertainty of escalation factor during the project lifetime and calculates the distribution for the cost. System application is demonstrated using a numerical example. The system can be used by planners and cost estimators for budgeting the effect of cost escalation in large projects with multiyear schedules.     

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.     

工程总承包项目的成本管控策略

本文叙述了工程总承包项目的全面成本管控模式,在项目的整个运行周期内,如何在项目进行的各个阶段,以信息化系统为依托推进全员、全过程、全方位的成本管控体系。     

Improving Cost Estimates of Construction Projects Using Phased Cost Factors

Central to cost-based competition is the capability to accurately predict the cost of delivering a project. Most literature on cost estimation focuses on specific estimation methods as generic techniques and little attention has been paid to the unique requirements at each project stage. This note attempts to identify the critical factors for effective estimation at various stages of typical construction projects. Drawing from organization control theory and cost estimating literature, this note develops a theoretical framework that identifies the critical factors for effective cost estimation during each project phase of a conventional construction project. The underlying logic is that as a cost estimating effort progresses, both task programmability and output measurability improve. As a result, control effort will shift from input-oriented control to a combination of output and behavior control.     

Cost Information Model for Managing Multiple Projects

Construction companies must deal with several projects at once, but a system to manage multiple projects is not fully developed yet. The first step towards developing such system is to design an information model that is suitable for managing multiple projects. This paper presents the cost-based project modeling (CBPM) method in contrast to the traditional activity-based project modeling methods. The CBPM uses cost as a core of the model along with other project information organized around it. The CBPM serves as a platform for integrating project information from multiple projects. Various types of construction costs are hierarchically modeled to generate corporate-wide information such as project performances, cash flows, and other predictive indicators. Based on the information model, an object-oriented database was developed to contain cost data across several projects. In the model, a module that connects to external systems is built into the model to enhance interactivity with the legacy systems and the industry standards. A prototype system was developed and tested with actual project data to validate the information processing capabilities of the model. The findings from the test indicate construction cost can be an excellent medium that can organize various types of information of multiple projects.     

Time-Cost Optimization of Construction Projects with Generalized Activity Constraints

Time-cost analysis is an important element of project scheduling, especially for lengthy and costly construction projects, as it evaluates alternative schedules and establishes an optimum one considering any project completion deadline. Existing methods for time-cost analysis have not adequately considered typical activity and project characteristics, such as generalized precedence relationships between activities, external time constraints, activity planning constraints, and bonuses/penalties for early/delayed project completion that would provide a more realistic representation of actual construction projects. The present work aims to incorporate such characteristics in the analysis and has developed two solution methods, an exact and an approximate one. The exact method utilizes a linear/integer programming model to provide the optimal project time-cost curve and the minimum cost schedule considering all activity time-cost alternatives together. The approximate method performs a progressive project length reduction providing a near-optimal project time-cost curve but it is faster than the exact method as it examines only certain activities at each stage. In addition, it can be easily incorporated in project scheduling software. Evaluation results indicate that both methods can effectively simulate the structure of construction projects, and their application is expected to provide time and cost savings.     

Scheduling Resource-Constrained Projects with Ant Colony Optimization Artificial Agents

The paper presents a methodology to schedule resource-constrained construction projects by use of algorithms based on ant colony optimization (ACO); an artificial agent inspired by the collective behavior of natural ant colonies as they optimize their path from an origin (ant nest) to a destination (food source) by use of previously acquired knowledge. Further, to an application of the ACO artificial agent to a resource-unconstrained network topology, the method is applied to a resource-constrained network and utilized in examining the effects of resource availability constraints to critical path calculations and project completion time.     

Software for Planning and Cost Control in Directional Drilling Projects

As the complexity and size of the projects undertaken by horizontal directional drilling (HDD) contractors rapidly increase, there is a growing need for the development of dedicated software designed to meet the industry’s special needs and requirements. This paper presents the results of a survey of the HDD industry’s software needs as well as a summary of commercially available software specifically designed for this industry. In addition, the development of two computerized applications tailored for the HDD industry are described. The first of these applications is an integrated data management system that combines asset management, cost control, estimating, and project tracking capabilities, enabling decision makers to closely monitor field performance in terms of expenditure and productivity. The second application is a simulation model developed for optimizing the utilization of drilling rigs and hydro-vacuum trucks on large-scale urban projects. Both applications are designed to improve the planning, estimating, and productivity of directional drilling projects, ultimately reducing the cost of expanding underground infrastructure networks.     

Quantiative Methodology for Determination of Cost Contingency in International Projects

This paper presents a quantitative methodology to determine financial impacts of the risk factors during the bidding stages of international construction projects. Project and country data of 26 construction projects from 21 countries were collected for evaluation of the international risk factors. The factors impacting cost contingency were identified using correlation and regression analysis techniques. The results indicated that four factors had major contributions for explaining the variations in the contingency levels. A regression model including the significant factors was developed to support bidding contingency decisions. The methodology presented provides a robust and practical statistical approach for determination of contingency by focusing on important risk factors. Details regarding model development and validation are presented along with a discussion on study limitations.     

Rework in Civil Infrastructure Projects: Determination of Cost Predictors

Within Australia, civil engineering works continue to meet the insatiable demand for new infrastructure despite project complexity and cost and schedule overruns. A significant factor that can contribute to such overruns is rework; yet to date research into the root causes and consequential costs of rework in civil infrastructure projects has been limited. Using a questionnaire survey, rework costs and probable causes were obtained from 115 civil infrastructure projects. Stepwise multiple regression was then used to determine the significant variables that contributed to rework. The regression model revealed that the following five significant predictors accounted for 25% of the variance in total rework cost: (1) ineffective use of information technologies; (2) excessive client involvement in the project; (3) lack of clearly defined working procedures; (4) changes made at the request of the client; and (5) insufficient changes initiated by the contractor to improve quality. The findings also revealed that mean total rework costs were 10% of the contract value for the sample. Interestingly, the extent of rework experienced was significantly correlated with project cost and schedule growth (p<0.01). It is suggested that future work is required to determine the underlying factors that contribute to rework in civil infrastructure projects before effective preventive strategies can be identified.     

Estimation of Cost Contingency for Air Force Construction Projects

Risk and associated cost overruns are critical problems for construction projects, yet the most common practice for dealing with them is the assignment of an arbitrary flat percentage of the construction budget as a contingency fund. Therefore, our goal was to identify significant variables that may influence, or serve as indicators of, potential cost overruns. We analyzed data from 203 Air Force construction projects over a full range of project types and scopes using multiple linear regression to develop a model to predict the amount of required contingency funds. The proposed model uses only data that would be available prior to the award of a construction contract. The variables in the model were categorized as project characteristics, design performance metrics, and contract award process influences. Based on the performance metric used, the model captures 44% of actual cost overruns versus the 20% captured by the current practice. Furthermore, application of the model reduces the average contingency budgeting error from 11.2 to only 0.3%.     

中国二冶集团公司项目成本控制的研究

文章从搞好工程项目的成本控制首先应遵循成本控制的基本原则,把握成本控制的程序;其次充分认识、分析和找出企业在成本控制中的现状;并制定切实可行成本控制的措施,努力搞好事前计划、事中控制和事后总结分析3个方面,详细论述了如何进行企业项目工程成本控制,使施工企业获得最大利润。