• Proceedings of the Korean Institute of Building Construction Conference
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• 2009.05b
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• pp.159-162
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• 2009

Today's construction is more various and more complex. Because of that, a lot of uncertain factors are occurred and they related uncertain construction duration. For management complex architecture project, importance of construction schedule management also increased. In previous studies, one of solutions to overcome those problems is suggested. It was BIM based construction simulation process which focused on construction schedule and construction schedule management. But latest process had limited point which has no duration estimation function. So this paper suggested duration estimation method and developed duration estimation module. Duration estimation module developed with current scheduling tool MS Project and their macro function. However, this module has just developed Reinforced Concrete Structure and has to do more development and research.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.369-374
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• 2000

Despite their tilde application of some traditional project management techniques like the Program Evaluation and Review Technique, they lack of learning, one of important factors in many disciplines today due to a static view far prefect progression. This study proposes a framework for estimation by learning based on a Linear Bayesian approach. As a project progresses, we sequentially observe the durations of completed activities. By reflecting this newly available information to update the distribution of remaining activity durations and thus project duration, we can implement a decision support system that updates e.g. the expected project completion time as well as the probabilities of completing the project within talc due date and by a certain date. By Implementing such customized systems, project manager can be aware of changing project status more effectively and better revise resource allocation plans.

• Journal of KIISE:Software and Applications
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• v.31 no.1
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• pp.20-28
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• 2004

Estimation of software project cost, effort, and duration in the early stage of software development cycle is a difficult and key problem in software engineering. Most of development effort and duration estimation models presented by regression model of simple relation function point vs. effort and effort vs. duration instead of considering developer's productivity. But different project have need for different effort according to developer's productivity if the projects are same software size. Also, different duration takes according to developer's productivity if the projects require the same effort. Therefore, models that take into account of productivity have a limited application in actual development project. This paper presents models that can be estimate the duration according to productivity in order to compensate a shortcoming of the previous models. Propose model that could presume development period by various methods based on productivity and compared models' performance. As a result of performance comparison, an estimating model of development period from software size got simple and most good result. The model gives decision-making information of development duration to project management in the early stage of software life cycle.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.608-615
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• 2022

Construction projects are large-scale projects that require extensive construction costs and resources. Especially, scheduling is considered as one of the essential issues for project success. However, the schedule and resource management are challenging to conduct in high-tech construction projects including complex design of MEP and architectural finishing which has to be constructed within a limited workspace and duration. In order to deal with such a problem, this study suggests resource and sequence optimization using constraint programming in construction projects. The optimization model consists of two modules. The first module is the data structure of the schedule model, which consists of parameters for optimization such as labor, task, workspace, and the work interference rate. The second module is the optimization module, which is for optimizing resources and sequences based on Constraint Programming (CP) methodology. For model validation, actual data of plumbing works were collected from a construction project using a five-minute rate (FMR) method. By comparing actual data and optimized results, this study shows the possibility of reducing the duration of plumbing works in construction projects. This study shows decreased overall project duration by eliminating work interference by optimizing resources and sequences within limited workspaces.

• Korean Journal of Construction Engineering and Management
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• v.17 no.3
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• pp.71-80
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• 2016

PERT(Project Evaluation and Review Technique) is typical method in order to probabilistically establish the schedule plan for large scale complex project or mega project. PERT technique is impossible to estimate relationship of each activity probabilistically when there are overlapping relationships because it is limited to Finish-to-Start(FS) relationship. In order to overcome this kind of limitation of PERT technique, PLET(Probabilistic Linkage Evaluation Technique) has been suggested to probabilistically estimate project duration for various overlapping relationships for each activity. However, estimating project duration by PLET technique only considers uncertainty of relationship between activities and not activity time, thus it is not the perfect duration estimating method. The main objective of this research is to propose the integration model of PERT and PLET and verify its probabilistic validity. By verifying application of time calculation method of integration model in practical case, this research will suggest probabilistic project duration estimating method in schedule plan of high-risk construction industry.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.2
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• pp.47-55
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• 2022

The objective of this study was to analyze the effect of the duration and time distribution of probability rainfall on farmland inundation for the paddy fields in the drainage improvement project site. In this study, eight drainage improvement project sites were selected for inundation modeling. Hourly rainfall data were collected, and 20- and 30-year frequency probability rainfalls were estimated for 14 different durations. Probability rainfalls were distributed using Intensity-Duration-Frequency (IDF) and Huff time distribution methods. Design floods were calculated for 48 hr and critical duration, and IDF time distribution and Huff time distribution were used for 48 hr duration and critical duration, respectively. Inundation modeling was carried out for each study district using 48 hr and critical duration rainfalls. The result showed that six of the eight districts had a larger flood discharge using the method of applying critical duration and Huff distribution. The results of inundation depth analysis showed similar trends to those of design flood calculations. However, the inundation durations showed different tendencies from the inundation depth. The IDF time distribution is a distribution in which most of the rainfall is concentrated at the beginning of rainfall, and the theoretical background is unclear. It is considered desirable to apply critical duration and Huff time distribution to agricultural production infrastructure design standards in consideration of uniformity with other design standards such as flood calculation standard guidelines.

• Korean Journal of Construction Engineering and Management
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• v.6 no.1 s.23
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• pp.73-79
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• 2005

This paper, introduces a Stochastic Project Scheduling Simulation system (SPSS III) developed by the author to predict a project completion probability in a certain time. The system integrates deterministic CPM, probabilistic PERT, and stochastic Discrete Event Simulation (DES) scheduling methods into one system. It implements automated statistical analysis methods for computing the minimum number of simulation runs, the significance of the difference between independent simulations, and the confidence interval for the mean project duration as well as sensitivity analysis method in What-if analyzer component. The SPSS 111 gives the several benefits to researchers in that it (1) complements PERT and Monte Carlo simulation by using stochastic activity durations via a web based JAVA simulation over the Internet, (2) provides a way to model a project network having different probability distribution functions, (3) implements statistical analyses method which enable to produce a reliable prediction of the probability of completing a project in a specified time, and (4) allows researchers to compare the outcome of CPM, PERT and DES under different variability or skewness in the activity duration data.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.892-896
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• 2005

This paper collected 132 schools reconstruction projects in central Taiwan, which received the most serious damage from the Chi-Chi Earthquake. Regression analysis was implemented to build the prediction model of the cost and the duration for the collected projects. It is found that the cubic regression models are capable for predicting the cost and the duration of the projects contracted by the central agency of which the contracting awarding approach was based on the most advantageous tendering (MAT) approach. On the other hand, power regression models are capable for predicting the cost and the duration of the projects contracted through the low bid tendering (LBT) approach. It is also found that the performance of the regression prediction model differs in accordance with organizations that contracted the reconstruction projects.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.597-600
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• 2008

Recently, Several Mega project are been performing as a multi-dimensional development project in Korea, but some problem has been revealed about deficiency of the history, experience, and skill. A multi-dimensional development project require the technology which can manage mega project to its specific at the level of program management. predicting schedule and schedule management are the most important for mega project, been performing over several years. This research shows the method of predicting and planning schedule in the early stage as a pre-study on developing a technology of schedule management. First of all, it presents the development of database considering the specific of mega project that can accumulate the history of schedule and search the schedule according to the type of single and multi building. Also it suggests the method of prediction schedule by creating scenarios according to owner requirements and cash flow, affecting schedule management in the early stage, and the shortening possibility of schedule duration using CCPM theory.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.410-420
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• 1994

In many project-oriented production systems, e.g., shipyards or large-scale steel products manufacturing, resource loading by an activity is flexible, and the activity duration is a function of resource allocation. For example, if one doubles the size of the crew assigned to perform an activity, it may be feasible to complete the activity in half the duration. Such flexibility has been modeled by Weglarz [131 and by Leachman, Dincerler, and Kim [7] in extended formulations of the resource-constrained project scheduling problem. This paper presents a new algorithmic approach to the problem that combines the ideas proposed by the aforementioned authors. The method we propose involves a two-step approach: (1) solve the resource-constrained scheduling problem using a heuristic, and (2) using this schedule as an initial feasible solution, find improved resource allocations by solving a linear programming model. We provide computational results indicating the superiority of this approach to previous methodology for the resource-constrained scheduling problem. Extensions to the model to admit overlap relationships of the activities also are presented.