Scheduling Of Repetitive Construction Projects Research Articles

Optimum planning and scheduling of repetitive construction projects: multi-objective optimization using the cuckoo search algorithm

Optimum planning and scheduling of repetitive construction projects: multi-objective optimization using the cuckoo search algorithm

Scheduling of repetitive construction projects using geographic information systems: an integration of critical path method and line of balance

Critical path method (CPM) is the widely used technique for scheduling of non-repetitive construction projects, on the other hand, line of balance (LOB) is used for scheduling of repetitive construction projects. There may exist repetitive and non-repetitive parts together in a construction project. In the present study, to schedule repetitive and non-repetitive parts of a construction project together, CPM and LOB techniques have been integrated within the geographic information systems (GIS) environment. The scheduling tool has been developed in which activities of a repetitive part are scheduled using CPM and different repetitive parts are scheduled using LOB. A sample project scheduled using CPM technique takes 520 days, however, if the same project is scheduled using the developed tool takes 214 days. Further, construction planning is not done in isolation, that is, without considering surroundings of a construction project under consideration. The scheduling tool developed in GIS environment considers the effect of surroundings on the developed integrated schedule. A link has been established between the activities of the developed schedule and corresponding 3D components in GIS environment to develop 4D model of execution sequence of a construction project. This facilitates in checking logical errors, resource continuity, and incompleteness of the developed integrated schedule.

Delay Risk Assessment of Repetitive Construction Projects Using Line-of-Balance Scheduling and Monte Carlo Simulation

AbstractAlthough the line-of-balance (LOB) method is widely used for the scheduling of repetitive construction projects, there are only a limited number of studies that deal with the issue of how t...

Optimizing the Scheduling of Repetitive Construction to Minimize Interruption Cost

AbstractThis paper presents the development of a novel optimization model for the scheduling of repetitive construction projects. The model provides original and unique capabilities that enable pla...

Opposition multiple objective symbiotic organisms search (OMOSOS) for time, cost, quality and work continuity tradeoff in repetitive projects

AbstractConstruction managers often face with projects containing multiple units wherein activities repeat from unit to unit. Therefore effective resource management is crucial in terms of project duration, cost and quality. Accordingly, researchers have developed several models to aid planners in developing practical and near-optimal schedules for repetitive projects. Despite their undeniable benefits, such models lack the ability of pure simultaneous optimization because existing methodologies optimize the schedule with respect to a single factor, to achieve minimum duration, total cost, resource work breaks or various combinations, respectively. This study introduces a novel approach called “opposition multiple objective symbiotic organisms search” (OMOSOS) for scheduling repetitive projects. The proposed algorithm used an opposition-based learning technique for population initialization and for generation jumping. Further, this study integrated a scheduling module (M1) to determine all project objectives including time, cost, quality and interruption. The proposed algorithm was implemented on two application examples in order to demonstrate its capabilities in optimizing the scheduling of repetitive construction projects. The results indicate that the OMOSOS approach is a powerful optimization technique and can assist project managers in selecting appropriate plan for project.Highlights This study presents an advanced multiple optimization algorithm OMOSOS. Opposition technique is utilized to spreading the initial population and generation jumping. OMOSOS is applied to solve time, cost, quality and work continuity tradeoff problem. The model performance is demonstrated in the experimental results.

Optimized scheduling and buffering of repetitive construction projects under uncertainty

Purpose Construction projects are complex projects taking place in dynamic environments, which necessitates accounting for different uncertainties during the planning stage. There is a significant lack of management tools for repetitive projects accounting for uncertainties in the construction environment. The purpose of this paper is to present an algorithm for the optimized scheduling of repetitive construction projects under uncertainty. Design/methodology/approach Fuzzy set theory is utilized to model uncertainties associated with various input parameters. The developed algorithm has two main components: optimization component and buffering component. The optimization component presents a dynamic programming approach that processes fuzzy numbers. The buffering component converts the optimized fuzzy schedule into a deterministic schedule and inserts time buffers to protect the schedule against anticipated delays. Agreement Index (AI) is used to capture the user’s desired level of confidence in the produced schedule while sizing buffers. The algorithm is capable of optimizing for cost or time objectives. An example project drawn from literature is analysed to demonstrate the capabilities of the developed algorithm and to allow comparison of results to those previously generated. Findings Testing the algorithm revealed several findings. Fuzzy numbers can be utilized to capture uncertainty in various inputs without the need for historical data. The modified algorithm is capable of optimizing schedules, for different objectives, under uncertainty. Finally AI can be used to capture users’ desired confidence in the final schedule. Originality/value Project planners can utilize this algorithm to optimize repetitive projects schedules, while modelling uncertainty in different input parameters, without the need for relevant historical data.

Automated trade‐off between time and cost in planning repetitive construction projects

An automated model is developed to support the optimization of the planning and scheduling of repetitive construction projects. The model provides the capability of optimizing two important objectives commonly sought in scheduling repetitive construction projects: minimizing project duration; and minimizing project cost. The model performs this multi‐objective optimization using a genetic algorithm approach. The output of the model is a set of optimal solutions that represent the trade‐off between time and cost in planning repetitive construction projects. Furthermore, the model can be utilized to find a single scheduling solution that provides the minimum overall project cost by simply adding project indirect cost to the obtained project direct cost for each of the obtained scheduling solutions on the Pareto optimal curve. Other important time‐related costs are also considered in the model including: early completion incentives, late completion penalties and lane rental costs. Providing the planners of repetitive construction projects with an automated set of optimal time–cost trade‐off solutions should contribute to cost‐effective and speedy delivery of this type of construction project. An application example is analysed to illustrate the use of the model and demonstrate its capabilities in generating optimal trade‐off solutions between minimizing the project time and cost for repetitive construction projects.

A GA optimization model for workgroup-based repetitive scheduling (WoRSM)

Most construction repetitive scheduling methods developed so far have been based on the premise that a repetitive project is comprised of many identical production units. Recently Huang and Sun [Huang RY, Sun KS. Non-unit based planning and scheduling of repetitive construction project. J Constr Eng Manage ASCE 2006;132(6):585–97] developed a workgroup-based repetitive scheduling method that takes the view that a repetitive construction project consists of repetitive activities of workgroups. Instead of repetitive production units, workgroups with repetitive or similar activities in a repetitive project are identified and employed in the planning and scheduling. The workgroup-based approach adds more flexibility to the planning and scheduling of repetitive construction projects and enhances the effectiveness of repetitive scheduling. This work builds on previous research and develops an optimization model for workgroup-based repetitive scheduling. A genetic algorithm (GA) is employed in model formation for finding the optimal solution. A chromosome representation, as well as specification of other parameters for GA analysis, is described in the paper. A sample case study is used for model validation and demonstration. Results and findings are reported.

An optimization model for workgroup-based repetitive scheduling

Most construction repetitive scheduling methods developed so far have been based on the premise that a repetitive project is comprised of many identical production units. Recently, Huang and Sun (2005) developed a workgroup-based repetitive scheduling method that takes the view that a repetitive construction project consists of repetitive activities of workgroups. Instead of repetitive production units, workgroups with repetitive or similar activities in a repetitive project are identified and employed in the planning and scheduling. The workgroup-based approach adds more flexibility to the planning and scheduling of repetitive construction projects and enhances the effectiveness of repetitive scheduling. This work builds on previous research and develops an optimization model for workgroup-based repetitive scheduling. A genetic algorithm (GA) is employed in model formation for finding the optimal or near-optimal solution. A chromosome representation, as well as specification of other parameters for GA analysis, is described in the paper. Two sample case studies, one simple and one sewer system project, are used for model validation and demonstration. Results and findings are reported.Key words: construction scheduling, repetitive project, workgroup, optimization, genetic algorithm.

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.

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.

Critical Path Method–Line of Balance Model for Efficient Scheduling of Repetitive Construction Projects

A general model is presented for efficient scheduling and resource management in construction projects that involve a high degree of repetition, such as highways and pipelines. The proposed model has three main features: ( a) it fully integrates the critical path method for network analysis and the line of balance technique for linear scheduling, ( b) it allows realistic schedule development considering project deadline and resource constraints, and ( c) it incorporates improved schedule presentation that shows crews’ movements along the repetitive units and their detailed work assignments. The detailed formulation of the proposed model is described, and an example application is presented. The proposed model is demonstrated to offer significant advantages as a resource-driven approach. Future extensions to the proposed model are then outlined.