Multi Objective Optimization for Scheduling Repetitive Projects Using GA

Mathew, Jeeno; Paul, Brijesh; J, Dileeplal; Mathew, T. Lazar

doi:10.1016/j.protcy.2016.08.209

Cited by 11 publications

(4 citation statements)

References 12 publications

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“…A mathematical model is proposed by Jeeno Mathew et al [21] to solve the problem for satisfying the objectives like minimizing total project task time, total expenditure of the project and minimize both expenditure and task time on a repetitive project scheduling problem with the constraints of precedence connectivity among different tasks and precedence connectivity among different sites. In addition to the above mentioned objectives, the penalty cost corresponding to each task in every lagging project site is considered.…”

Section: Modelmentioning

confidence: 99%

“…For the proposed algorithm validation and comparison, a repetitive project scheduling problem with multiple crew option in each activity is considered. A project consists of 18 tasks in a project site and five repetitive sites in which work is going on with the input data taken from Jeeno Mathew et al [21] as shown in Table I, Table II and Table III where "N1, N2, N3…." are different tasks, "S1, S2, S3…."…”

Section: Computational Studymentioning

confidence: 99%

“…R.Y Huang et al [11] developed a technique to maximize the NPV in a repetitive project industry where the best possible work arrangement between workgroups is accommodating and keeping up work progression of resources. S.L Fan et al [12] also built up a model similar to the previous one where the goal is to minimize the total project expenditure Jeeno Mathew et al [21] developed a genetic algorithm based methodology for scheduling repetitive projects in which penalty cost is also considered. An optimization software (OSS) was developed by Remon Fayek Aziz [13] for maximizing the NPV of a project.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Crew Model using GAIIPDM in Repetitive Projects

Mathew*¹,

Paul²

2019

IJRTE

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 Abstract: Several indistinguishable or comparative tasks/works in a project are generally alluded to as repetitive projects. A project have group of tasks which is repetitive in nature in all over the project or a similar plan in different positions are commonly known as repetitive project. In repetitive project businesses, distinctive crew choices are accessible for each task, and selecting the best choice to a task is a noteworthy test for administrators of a project. Since acquiring optimum results is found computationally escalated for this type of problems, a modified Genetic Algorithm based technique is developed to schedule projects to satisfy different goals like minimizing total task time and the total expenditure of the project, with the constraints of precedence connections between different tasks, precedence connections between different sites and the due time within which different tasks to be finished. The performance of the proposed method is compared with solutions created using existing algorithms like simple GA and ABC. Exact solutions generated by solving the developed mathematical model is utilized for validating the solutions acquired by modified GA. The computational outcomes demonstrate that the proposed GAIIPDM methodology performs significantly well in terms of quality of solutions.

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Section: Modelmentioning

confidence: 99%

Section: Computational Studymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Crew Model using GAIIPDM in Repetitive Projects

Mathew*¹,

Paul²

2019

IJRTE

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“…RPs often require resources (such as crews) to perform the same task in various units (locations, segments) by moving from one unit to the next (Vanhoucke, 2006). Several repetitive scheduling methods (RSMs) have been proposed for the planning and scheduling of repetitive construction projects (Huang & Sun, 2005;Jeeno, Brijesh, Dileeplal, & Tinjumol, 2016;Khalied & Khaled, 2006;Photios & Yang, 2016). The general consensus is that RSMs are simple and easily applied scheduling methodology that follows naturally from the concepts and relationships found in the PDM (Harris & Ioannou, 1998).…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Symbiotic Organisms Optimization for Making Time-Cost Tradeoffs in Repetitive Project Scheduling Problem

Tran

Chou

Luong

2019

Journal of Civil Engineering and Management

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Time-cost problems that arise in repetitive construction projects are commonly encountered in project scheduling. Numerous time-cost trade-off approaches, such as mathematical, metaheuristic, and evolutionary methods, have been extensively studied in the construction community. Currently, the scheduling of a repetitive project is conducted using the traditional precedence diagramming method (PDM), which has two fundamental limitations: (1) progress is assumed to be linear from start to finish; and (2) activities in the schedule are connected each other only at the end points. This paper proposes a scheduling method that allows the use of continuous precedence relationships and piece-wise linear and nonlinear activity-time-production functions that are described by the use of singularity functions. This work further develops an adaptive multiple objective symbiotic organisms search (AMOSOS) algorithm that modifies benefit factors in the basic SOS to balance exploration and exploitation processes. Two case studies of its application are analyzed to validate the scheduling method, as well as to demonstrate the capabilities of AMOSOS in generating solutions that optimally trade-off minimizing project time with minimizing the cost of non-unit repetitive projects. The results thus obtained indicate that the proposed model is feasible and effective relative to the basic SOS algorithm and other state-of-the-art algorithms.

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Multi-objective Resource-Constrained Scheduling in Construction Projects

Lazari

Chassiakos

2020

Collaboration and Integration in Construction, Engineering, Management and Technology

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Multi Objective Optimization for Scheduling Repetitive Projects Using GA

Cited by 11 publications

References 12 publications

A Crew Model using GAIIPDM in Repetitive Projects

A Crew Model using GAIIPDM in Repetitive Projects

Multi-Objective Symbiotic Organisms Optimization for Making Time-Cost Tradeoffs in Repetitive Project Scheduling Problem

Multi-objective Resource-Constrained Scheduling in Construction Projects

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