Scheduling Of Repetitive Projects Research Articles

Scheduling of Repetitive Projects with Multiple Objectives by Multiple Crew Model

Scheduling of Repetitive Projects with Multiple Objectives by Multiple Crew Model

Optimization Study of Construction Repetitive Project Scheduling Based on Big Data Background

This paper proposes the use of LOB method for repetitive project scheduling solution, and the use of branch limit algorithm to optimize LOB resource allocation to provide the best resource distribution scheme for construction projects. The control process types are analyzed and the time parameters of the LOB method are calculated. Introduce the resource constraint problem of repetitive projects, establish the objective function, put forward the relevant constraints of LOB resource allocation, combine the branching strategy, limiting strategy and pruning strategy, and construct the resource allocation process of LOB scheduling based on the branching and limiting algorithm. Select the parameters number of processes ($n$), maximum employable amount of processes ( k j ), and deadline tightness ( θ ), and conduct random generation tests to compare the performance of different LOB scheduling methods. The LOB scheduling schedule problem is described in the context of a construction project example, and the LOB resource allocation problem is solved by the branch-and-bound algorithm to obtain the optimal resource allocation scheme. Calculate the duration of each process after transformation is 12, 23, 13, 17.1, 12, 12. And the end time of the last process is 44.3, which satisfies the contract duration.

Review of Research on Uncertain Repetitive Project Scheduling

With the continuous development of project management practice, the project often suffers from disturbance events in the actual execution activity, which leads to project delay and great economic losses.Uncertainty project scheduling studies have also received attention.Repetitive project is a type of project with its own characteristics in which the construction site can be divided into several independent units and all activities are repetitive on multiple units, such as high-rise buildings, highways, and pipeline works. The characteristics of repetitive project controlling paths and controlling activities have their own advantages in responding to uncertain events. This paper takes repetitive project scheduling as the object to sort out its uncertain scheduling research. Firstly, the uncertain research based on probability random theory, fuzzy set theory and robustness theory is summarized, and then the research on different scheduling strategies such as interruptions soft logic and multi-mode in repetitive project scheduling is further summarized. Finally, the current research status of uncertain reactive scheduling is summarized,and further research directions are pointed out.

Optimization Study on Carbon Trading and Constructive Repetitive Project Scheduling in the Context of Internet Era

Abstract This paper constructs a carbon trading market trade-off problem model based on the time-constrained relationship of process families in RSM. By analyzing the repetitive construction project processes, linear, block, and strip processes are refined. The time-constrained relationship between process families in the RSM is studied, and the expression formula is derived. Process continuity and resource continuity in repetitive construction projects are analyzed to reduce the time required to complete a unit of work. The process duration of the project is determined by optimizing the amount of new resources and human resources used. The results show that when the length of the carbon emission interval is at (0.5, 2]t, when the length of the carbon emission interval is small, the role of RSM process time carbon trading price is larger.

Optimized crew selection for scheduling of repetitive projects

PurposeThe purpose of this paper is to identify optimum crew formations at unit execution level of repetitive projects that minimize project duration, project cost, crew work interruptions and interruption costs, simultaneously.Design/methodology/approachThe model consists of four modules. The first module quantifies uncertainties associated with the crew productivity rate and quantity of work using the fuzzy set theory. The second module identifies feasible boundaries for activity relaxation. The third module computes direct cost, indirect cost and interruption costs, including idle crew cost as well as mobilization and demobilization costs. The fourth module identifies near-optimum crew formation using a newly developed multi-objective optimization model.FindingsThe developed model was able to provide improvements of 0.2, 16.86 and 12.98% for minimization of project cost, crew work interruptions and interruption costs from US$1,505,960, 8.3 days and US$8,300, as recently reported in the literature, to US$1,502,979, 6.9 days and US$7,222, respectively, without impacting the optimized project duration.Originality/valueThe novelty of this paper lies in its activity-relaxation free float that considers the effect of postponing early finish dates of repetitive activities on crew work interruptions. The introduced new float allows for calculating the required crew productivity rate that minimizes crew work interruptions without delaying successor activities and without impacting the optimized project duration. It safeguards against assignment of unnecessary costly resources.

Optimizing non-unit repetitive project resource and scheduling by evolutionary algorithms

Repetitive project scheduling is a frequently encountered and challenging task in project planning. Researchers have developed numerous methods for the scheduling and planning of repetitive construction projects. However, almost all current repetitive scheduling methods are based on identical production units or they neglect the priorities of activities. This work presents a new hybrid evolutionary approach, called the fuzzy clustering artificial bee colony approach (FABC), to optimize resource assignment and scheduling for non-unit repetitive projects (NRP). In FABC, the fuzzy c-means clustering technique applies several multi-parent crossover operators to utilize population information efficiently and to improve convergence efficiency. The scheduling subsystem considers the following: (1) the logical relationships among activities throughout the project; (2) the assignment of multiple resources; and (3) the priorities of activities in groups to calculate project duration. Two numerical case studies are analyzed to demonstrate the use of the FABC-NRP model and its ability to optimize the scheduling of non-unit repetitive construction projects. Experimental results indicate that the proposed method yields the shortest project duration on average and deviation of optimal solution among benchmark algorithms considered herein and those considered previously. The outcomes will help project managers to prepare better schedules of repetitive projects.

Space-Time Repetitive Project Scheduling Considering Location and Congestion

AbstractRepetitive projects account for a large proportion of construction projects. Different from standard project scheduling problems, scheduling such projects requires considering both location...

Resource Allocation in a Repetitive Project Scheduling Using Genetic Algorithm

Resource Allocation is procedure of doling out or allocating the accessible assets in a monetary way and productive way. Resource allocation is the scheduling of the accessible assets and accessible exercises or activities required while thinking about both the asset accessibility and the total project completion time. Asset provisioning and allocation takes care of that issue by permitting the specialist co-ops to deal with the assets for every individual demand of asset. A probabilistic selection procedure has been developed in order to ensure various selections of chromosomes

Integration of linear scheduling method and the critical chain project management

Integration of repetitive and non-repetitive scheduling methods utilizes the merits and unique features of those methods. This paper presents a new scheduling method for repetitive projects that integrates linear scheduling (LSM) and critical chain project management (CCPM) methods. The proposed method introduces a framework for scheduling of repetitive projects; accounting for constraints of resources continuity and uncertainties associated with activity durations. It introduces a new buffer, named resource conflict buffer (RCB) to account for delays that may occur due to conflict in controlling resources among successor and predecessor activities. The developed method provides a systematic procedure for identifying several critical chains to replace the visual identification method that is currently used in linear scheduling. The features of the proposed method are illustrated in a case example for scheduling of repetitive projects using an integration of LSM and CCPM scheduling techniques. A discussion of results is performed and conclusions are drawn to highlight the features and capabilities of the proposed method.

A trade-off between time and cost in scheduling repetitive construction projects

The discrete time/cost trade-off problem (DTCTP) is commonly encountered in repetitive project scheduling. The current models for this problem assume that logical sequences of activities cannot be changed in different units. However, logical sequences are often changed to shorten the project time and minimize project total cost in many practical situations. This characteristic of repetitive activities is referred to as the soft logic. This paper presents a mixed integer nonlinear programming model that combines the general DTCTP and the concept of soft logic. The execution modes of an activity in different units are also considered. The DTCTP is known to be strongly NP-hard, and the introduction of soft logic makes it even more complex. A genetic algorithm (GA) is proposed to resolve the problem. The effectiveness of the proposed GA is verified using the example of a bridge construction project presented in the previous literature. The model proposed in this paper provides more flexibility to reduce the total cost and time of a repetitive project for the planners.

Resource Continuity Constraints in Repetitive Project Scheduling

In projects with repeating activities and in which the duration of activity unit has been influenced by resource-constrained, 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, in this paper we present a cloud genetic algorithm for repetitive project scheduling, in which considering Resource continuity constraints in Repetitive Project scheduling to solve the problem. An example application is presented to illustrate implementation and features of the proposed model. Finally, the relationship of duration and limited amount of resources have been analyzed.

LOB and CPM Integrated Method for Scheduling Repetitive Projects

Repetitive projects require schedules that ensure the uninterrupted usage of resources from a unit to similar units in a repetitive activity while maintaining logical dependency constraints. The critical path method (CPM) is the most widely used and accepted planning and scheduling method for traditional (nonrepetitive) projects. However, CPM does not suit the planning and scheduling needs of repetitive projects. Consequently, resource-driven techniques, such as line of balance (LOB), have been used to schedule repetitive projects that ensure work continuity. LOB is primarily a graphical technique that lacks the analytical qualities of CPM scheduling. A need for an analytical technique fulfilling characteristics of repetitive projects has been reported in the literature. Few attempts have been made to combine the benefits of CPM and LOB techniques in planning and scheduling of repetitive projects. In this paper, an integrated CPM and LOB model has been developed to schedule repetitive projects in an easy nongraphical manner, considering both logic dependency and resource continuity constraints. Overlapping activities of a single typical unit are used to model duration and logical relationships of repetitive activities. The proposed model essentially consists of four steps. In the first step, basic LOB calculations are performed to ensure resource continuity. Activity duration along all repetitive units is calculated in the second step. In the third step, overlapping activities are used to model logical relationships between consecutive activities. Next, CPM time analysis is performed to specify activities’ timings and floats and project completion time. An example application is presented to illustrate implementation and features of the proposed model.

Controlling Path and Controlling Segment Analysis in Repetitive Scheduling Method

AbstractThe controlling path and controlling segment are the basis for repetitive project scheduling. In this paper the controlling path is defined as the longest path in duration that determines the minimum project duration, including the controlling segments and controlling constraints on it. The controlling segments are defined as the subactivities on the controlling path. A method to identify the controlling path and controlling segments is proposed, on the basis of the technology of identifying the potential controlling points. To investigate how the project duration is determined, three types of controlling segments are defined and analyzed, namely, the forward controlling segment, the point controlling segment, and the backward controlling segment. This paper presents a convenient and correct way to identify the controlling path and controlling segments conforming to the constraints of projects.

Productivity Scheduling Method Compared to Linear and Repetitive Project Scheduling Methods

The analysis of project schedules is among the central tasks of construction managers. Parallel to the well-known critical path method, linear scheduling techniques have been researched. The two most fully developed existing methods, the linear scheduling model and the repetitive scheduling method, are reviewed. Based on a discussion of a published example, the new mathematical analysis method for linear and repetitive schedules is introduced. The productivity scheduling method is based on singularity functions that provide a flexible and powerful mathematical model for construction activities and their buffers that are characterized by their linear or repetitive nature. The steps of formulating initial equations, stacking and consolidating them, and deriving information about their criticality are described in detail. The mathematical approach of the new method allows an integrated treatment of activities regardless of the number of changes in productivity within them and does not depend on the graphical representation of the schedule.

Multiobjective optimization in Linear Repetitive Project scheduling

The Critical Path Method (CPM) and the Repetitive Scheduling Method (RSM) are the most often used tools for the planning, scheduling and control Linear Repetitive Projects (LRPs). CPM focuses mostly on project’s duration and critical activities, while RSM focuses on resource continuity. In this paper we present a linear programming approach to address the multi objective nature of decisions construction managers face in scheduling LRPs. The Multi Objective Linear Programming model (MOLP-LRP) is a parametric model that can optimize a schedule in terms of duration, work-breaks, unit completion time and respective costs, while at the same time the LP range sensitivity analysis can provide useful information regarding cost tradeoffs between delay, work-break and unit delivery costs. MOLPS-LRP can generate alternative schedules based on the relative magnitude and importance of different cost elements. In this sense it provides managers with the capability to consider alternative schedules besides those defined by minimum duration (CPM) or minimum resource work-breaks (RSM). Demonstrative results and analysis are provided through a well known in the literature case study example.

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.

System development for non-unit based repetitive project scheduling

Repetitive activities are commonly found in construction projects. It is stated in many literatures that repetitive scheduling methods are more effective than traditional CPM 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 and a prototype system are developed for the planning and scheduling of repetitive projects. Instead of repetitive production units, repetitive or similar activity groups are identified and employed for scheduling. The developed system 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 is conducted for system validation, as well as for demonstration. Application of repetitive scheduling methods can be facilitated with the developed system.

Scheduling of Repetitive Projects with Cost Optimization

Existing dynamic programming formulations are capable of identifying, from a set of possible alternatives, the optimum crew size for each activity in a repetitive project. The optimization criterion of these formulations is, however, limited to the minimization of the overall duration of the project. While this may lead to the minimization of the indirect cost of the project, it does not guarantee its overall minimum cost. The objective of this paper is to present a model that incorporates cost as an important decision variable in the optimization process. The model utilizes dynamic programming and performs the solution in two stages: first a forward process to identify local minimum conditions, and then a backward process to ensure an overall minimum state. In the first stage, a process similar to that used in time‐cost trade‐off analysis is employed, and a simple scanning and selecting process is used in the second stage. An example project from the literature is analyzed in order to demonstrate the use of the model and its validity, and illustrate the significance of cost as a decision variable in the optimization process.

Least cost scheduling for repetitive projects

Dynamic programming has been utilized to optimize scheduling of repetitive projects. The optimization criterion of existing techniques, however, is limited to minimizing the project duration and does not account for the impact of such optimization on the project cost. While the minimization of the project duration may reduce the project indirect costs, it does not guarantee a minimum total cost for the project. In practice, minimizing the overall cost of a project is frequently regarded to be more important than minimizing its duration. The objective of this paper is to present a flexible model that incorporates cost in the optimization process. In addition, the model is capable of considering the weather impact and the learning curve effect in the optimization process, simulating two important factors affecting productivity on this class of projects. The model utilizes dynamic programming and performs the solution in two stages: first, a forward path to identify local minimum conditions; and then a backward path to ensure a global minimum state. A numerical example from the literature is analyzed in order to demonstrate the use of the model, test its validity, and illustrate the significance of incorporating cost, weather impact, and the learning curve effect in the optimization process. Key words: planning and scheduling, repetitive projects, linear scheduling, cost optimization, dynamic programming, learning curve effect, weather impact.