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- W3116401525 abstract "Project scheduling provides a good insight for the manager to complete the project on time. Project scheduling gives complete timing analysis of activities involved and identifies the critical ones. Critical Path Method (CPM) is the most widely used in planning and scheduling method for traditional (non-repetitive) projects to determine the critical path which determines the minimum completion time of a project.Some construction projects consist of several similar or identical units, which are called repetitive projects. LOB technique has some drawbacks such inability to generate a clear critical path of the project schedule and calculating the total float because it is a graphical technique. LOB used for scheduling repetitive typical projects because this technique considered work continuity and resource availability constraints to avoid unnecessary crew idle time.Some of the previous studies have been made to combine the benefits of CPM and LOB techniques in planning and scheduling repetitive construction projects, so, there is a model that was developed for this objective (schedule repetitive projects in an easy non-graphical manner). But, in real life, more conditions contributed to varying activity duration. Thus, the duration of project activities contains some sort of uncertainty affecting the estimating of project duration. Previous studies used fuzzy set theory instead of probability theory for quantifying the uncertainty associated with the duration of project activities.In this paper, a developed integrated model of CPM and LOB with fuzzy time data for scheduling repetitive projects is presented. The developed model provides a new technique to schedule repetitive projects with fuzzy time data in an easy non-graphical manner." @default.
- W3116401525 created "2021-01-05" @default.
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- W3116401525 date "2020-12-01" @default.
- W3116401525 modified "2023-09-23" @default.
- W3116401525 title "Modeling of CPM/LOB integrated Scheduling Technique for Repetitive Construction Projects: Case of Multiple-Crews with Fuzzy Time Data" @default.
- W3116401525 cites W2017314337 @default.
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- W3116401525 doi "https://doi.org/10.21608/erjeng.2020.131424" @default.
- W3116401525 hasPublicationYear "2020" @default.
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