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.     

Multiobjective Evolutionary Finance-Based Scheduling: Entire Projects’ Portfolio

A strength Pareto evolutionary algorithm (SPEA) is proposed and was modified by incorporating logic-preserving crossover and mutation operators and employed to devise a set of optimum finance-based schedules of multiple projects being implemented simultaneously by a construction contractor. The problem involves the minimization of the conflicting objectives of financing costs, duration of the group of projects, and the required credit. The modified SPEA was employed to obtain the Pareto-optimal fronts for the two-objective combinations as well as the three objectives. In addition, a fuzzy-based technique was used to help the contractors select the best compromise solution over the Pareto-optimal solutions. The proposed approach has been developed and implemented on projects with different sizes. The results obtained by the modified SPEA, fuzzy-based approach demonstrated its potential and effectiveness in finance-based scheduling of multiple projects.     

Use of Genetic Algorithms in Resource Scheduling of Construction Projects

This paper presents an augmented Lagrangian genetic algorithm model for resource scheduling. The algorithm considers scheduling characteristics that were ignored in prior research. Previous resource scheduling formulations have primarily focused on project duration minimization. Furthermore, resource leveling and resource-constrained scheduling have traditionally been solved independently. The model presented here considers all precedence relationships, multiple crew strategies, total project cost minimization, and time-cost trade-off. In the new formulation, resource leveling and resource-constrained scheduling are performed simultaneously. The model presented uses the quadratic penalty function to transform the resource-scheduling problem to an unconstrained one. The algorithm is general and can be applied to a broad class of optimization problems. An illustrative example is presented to demonstrate the performance of the proposed method.     

Comparing Schedule Generation Schemes in Resource-Constrained Project Scheduling Using Elitist Genetic Algorithm

An issue has arisen with regard to which of the schedule generation schemes will perform better for an arbitrary instance of the resource-constrained project scheduling problem (RCPSP), which is one of the most challenging areas in construction engineering and management. No general answer has been given to this issue due to the different mechanisms between the serial scheme and the parallel scheme. In an effort to address this issue, this paper compares the two schemes using a permutation-based Elitist genetic algorithm for the RCPSP. Computational experiments are presented with multiple standard problems. From the results of a paired difference experiment, the algorithm using the serial scheme provides better solutions than the one using the parallel scheme. The results also show that the algorithm with the parallel scheme takes longer to solve each problem than the one using the serial scheme.     

Finance-Based Scheduling of Construction Projects Using Integer Programming

Construction scheduling is the process of devising schemes for sequencing activities. A realistic schedule fulfills the real concerns of users, thus minimizing the chances of schedule failure. The minimization of total project duration has been the concept underlying critical-path method/program evaluation and review technique (CPM/PERT) schedules. Subsequently, techniques including resource management and time-cost trade-off analysis were developed to customize CPM/PERT schedules in order to fulfill users’ concerns regarding project resources, cost, and time. However, financing construction activities throughout the course of the project is another crucial concern that must be properly treated otherwise, nonrealistic schedules are to be anticipated. Unless contractors manage to procure adequate cash to keep construction work running according to schedule, the pace of work will definitely be relaxed. Therefore, always keeping scheduled activities in balance with available cash is a potential contribution to producing realistic schedules. This paper introduces an integer-programming finance-based scheduling method to produce financially feasible schedules that balance the financing requirements of activities at any period with the cash available during that same period. The proposed method offers twofold benefits of minimizing total project duration and fulfilling finance availability constraints.     

Fast and Accurate Risk Evaluation for Scheduling Large-Scale Construction Projects

This paper presents the development of a novel probabilistic scheduling model that enables fast and accurate risk evaluation for large-scale construction projects. The model is designed to overcome the limitations of existing probabilistic scheduling methods, including the inaccuracy of the program evaluation and review technique (PERT) and the long computational time of the Monte Carlo simulation method. The model consists of three main modules: PERT model; fast and accurate multivariate normal integral method; and a newly developed approximation method. The new approximation method is designed to focus the risk analysis on the most significant paths in the project network by identifying and removing insignificant paths that are either highly correlated or have high probability of completion time. The performance of the new model is analyzed using an application example. The results of this analysis illustrate that the new model was able to reduce the computational time for a large-scale construction project by more than 94% while keeping the error of its probability estimates to less than 3%, compared with Monte Carlo Simulation methods.     

Survey of the Construction Industry Relative to the Use of CPM Scheduling for Construction Projects

While critical-path method (CPM) scheduling has been around since the 1950s, its application in the construction industry has still not received 100% acceptance or consistency in how it is used. Project controls, and CPM scheduling in particular, have gone unchanged in the standards arena with little focus for a common understanding and recognition of what is required for CPM schedule development, implementation, and use. In recent years, little research has been conducted relative to the use of CPM and its benefits. In order to determine how the industry views its applicability and usage, a survey was developed for the stakeholders in the construction industry. This paper summarizes extensive research that was performed of the construction industry relative to the use of CPM scheduling, its applicability and its acceptance in the execution of today’s constructed projects. The research obtained the stakeholders’ views on the use and effectiveness of CPM scheduling; the necessary qualifications of scheduling personnel; and opinions relative to whether standards and/or best practices are necessary. The paper discusses the different views of the stakeholders and recommendations as to how consistency can be obtained in the use of CPM scheduling in order to improve the construction industry.     

Investigating the Effectiveness of Certain Priority Rules on Resource Scheduling of Housing Estate Projects

The heuristic method is one of the methods used for the scheduling of resource-constrained projects. This method is commonly used in programming the projects with high number of activities and resources such as construction investments. This paper investigates the effectiveness of three heuristic method priority rules applied in the resource scheduling of ten Turkish housing estate projects which were scheduled according to three preselected priority rules [maximum remaining path length (MRPL), latest finish time (LFT), and minimum slack time (MNSLCK)] in resource-constrained conditions. The performance of each priority rule was evaluated in relation to the duration of the project. The results revealed that MRPL priority reduced the project duration to minimum in six projects, whereas LFT priority yielded the best duration results in three projects and MNSLCK priority in only one project.     

Construction Scheduling and Progress Control Using Geographical Information Systems

Traditional scheduling and progress control techniques such as bar charts and the critical path method (CPM) fail to provide information pertaining to the spatial aspects of a construction project. A system called PMS-GIS (Progress Monitoring System with Geographical Information Systems) was developed to represent construction progress not only in terms of a CPM schedule but also in terms of a graphical representation of the construction that is synchronized with the work schedule. In PMS-GIS, the architectural design is executed using a computer-aided drafting (CAD) program (AutoCAD), the work schedule is generated using a project management software (P3), the design and schedule information (including percent complete information) are plugged into a GIS package (ArcViewGIS), and for every update, the system produces a CPM-generated bar chart alongside a 3D rendering of the project marked for progress. The GIS-based system developed in this study helps to effectively communicate the schedule∕progress information to the parties involved in the project, because they will be able to see in detail the spatial aspects of the project alongside the schedule.     

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.     

Time-Profit Trade-Off Analysis for Construction Projects

This paper presents a multiobjective optimization model that provides new and unique capabilities including generating and evaluating optimal/near-optimal construction resource utilization and scheduling plans that simultaneously minimize the time and maximize the profit of construction projects. The computations in the present model are organized in three major modules: (1) a scheduling module that develops practical schedules for construction projects; (2) a profit module that computes the project profit; and (3) a multiobjective module that searches for and identifies optimal/near optimal trade-offs between project time and profit. A large-scale construction project is analyzed to illustrate the use of the model and to demonstrate its capabilities in generating and visualizing optimal trade-offs between construction time and profit.     

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.     

Critical Factors Affecting Schedule Performance: Evidence from Indian Construction Projects

Over 40% of Indian construction projects are facing time overrun ranging from 1 to 252 months; the reasons for which are being studied by researchers to suggest possible remedial measures. This paper identifies 55 attributes responsible for impacting performance of the projects. These attributes were then presented to Indian construction professionals in the form of a questionnaire. Statistical analysis of responses on the attributes segregated them into distinct sets of success attributes and failure attributes. Factor analysis of sets of success attributes and failure attributes separately grouped them into six critical success factors and seven critical failure factors. In order to understand the extent of contribution these factors have on the outcome of a construction project, a second stage questionnaire survey was also undertaken. The analyses of responses of the second stage questionnaire led us to conclude that two success factors and one failure factor: commitment of project participants; owner’s competence; and conflict among project participants contribute significantly in enhancement of current performance level of the project. The extent of their contribution has, however, been observed to vary for a given level of project performance. The analyses results are expected to help project professionals to focus on a few factors and get the optimum results rather than giving attention to all the factors and not getting the proportionate results.     

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.     

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.     

Electimize: New Evolutionary Algorithm for Optimization with Application in Construction Engineering

In nonlinear construction optimization problems, the capability of current optimization algorithms to find an optimal solution is usually limited by their inability to evaluate the effects of changing the value of each decision variable on reaching the optimal solution. This paper presents fundamental research aimed at developing a novel evolutionary optimization algorithm, named Electimize, that mimics the behavior of electrons flowing, through electric circuit branches with the least electric resistance. In the proposed algorithm, solutions are represented by electric wires and are evaluated on two levels: a global level, using the objective function, and a local level, evaluating the potential of each generated value for every decision variable. The paper presents (1) the research philosophy and scope, (2) the research methodology, and (3) the development of the algorithm. The proposed algorithm has been validated and applied successfully to an NP-hard cash flow optimization problem. The algorithm was able to find a better optimal solution and identified ten alternative optimal solutions for the same problem. This should prove useful in enhancing the optimization of complex large-scale problems.     

Linear Scheduling Using Optimal Control Theory

Construction planning and control literature reveal much effort in the recent past in the development of managerial control systems involving classical optimization techniques such as simulation, queuing theory, linear, dynamic programming, etc. Construction managers typically reach decisions in a perspective of time and in light of temporal criteria. The aforementioned techniques deal with the theoretical and computational aspects of time by static methods: Effects of one or more actions in a given interval are aggregated over time. Optimal Control Theory, a new branch of optimization, makes it possible to view the construction‐production process as a dynamic system that evolves over time. This paper presents a Continuous Optimal Control formulation of a hypothetical cut‐and‐fill job on a section of a highway. It is shown that Discrete Optimal Control framework is adequate for construction. The problem of scheduling the construction of a bridge due to Selinger is solved using this approach.     

Project Scheduling Using Fuzzy Set Concepts

Probabilistic methods are being used increasingly in construction engineering. However, when a parameter is expressed in linguistic rather than mathematical terms, classical probability theory fails to incorporate the information. The linguistic variables can be translated into mathematical measures using fuzzy set and system theory. A construction management problem, i.e., estimation of the duration of an activity, is solved using this theory. In order to implement the proposed technique, various membership functions need to be estimated using judgment or with the assistance of experts. The proposed technique is not sensitive to small variations in the membership values. This is a very desirable property. However, the method is sensitive to the choice of the fuzzy relations. The uncertainty in the fuzzy relations can be modeled along with other sources of uncertainty. The mean and variance of the parameters involved in the problem under consideration are estimated here using a new method. The method maximizes the product of the sum of the membership associations for a certain frequency of occurrence and the corresponding frequency of occurrence. One of the main advantages of the proposed technique is that it can be easily implemented in existing computer programs for project scheduling.     

Network Creation and Development for Repetitive-Unit Projects

Network scheduling is typically performed in three phases—network creation, analysis, and development. Although the critical path method (CPM) constitutes a well-established logic in network analysis, human intuition and experience are required for the creation and development of the network. Because of this, a variety of alternative CPM networks can be created in scheduling the same project. The use of the most desirable network can lead to a considerable reduction in the duration of the projects. This can be achieved by accurately identifying activities and linking them in an appropriate manner. Many researchers insisted that network scheduling lacks efficiency in scheduling repetitive-unit projects. Because of this, many scheduling methods have been developed to model such types of projects. However, most are not network based and require a large amount of input data, although most leading scheduling software remains network based and field engineers desire networklike forms of the schedule. In an effort to overcome this limitation, this paper presents a procedure for creating and developing networks for repetitive-unit projects. This network-based model incorporates a two-dimensional arrangement of activities, resource-space coordinates, for ease in creating a network and optimizes the activity linkage, thus resulting in the most desirable results. The model is applied to a typical repetitive-unit project to illustrate the use and capabilities of the model. The model can serve as an aid for inexperienced schedulers in creating a network as well as its optimization. An experienced scheduler can also check the desirability of his or her own created network via the use of this model.     

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.