• Korean Journal of Construction Engineering and Management
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• v.16 no.1
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• pp.35-43
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• 2015

It is important to have enough design and construction duration for infrastructure projects. However, recent water resource project in Korea shows several problems caused by their fast-tract schedule. National Audit Committee report several water resource projects have quality problems caused by insufficient project duration. Especially, water resource projects such as dam and water pipeline construction should have proper time to secure their structure quality. Normal project duration for these projects should be estimated based on previous similar projects' historical data analysis. However there is no standard model which can estimate normal project duration for water resource projects in Korea. There are several normal project duration estimation models for building project developed by public(LH) and private construction companies. However, there is no proper model for water resource projects. So, this study developed normal project duration model for dam and water pipeline projects using historical data and show application of models.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.780-785
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• 2005

This paper aims to consider an overall benefit-duration optimization (OBDO) problem for the sake of maximizing owner's economic benefits, whilst considering influences of schedule compression incurred opportunity income on the profitability of a large-scale construction project. Unlike previous schedule optimization models and techniques that have focused on project duration or cost minimization, with greater weight on contractors' interests, OBDO facilitates owner's economic benefits through overall benefit-duration optimization. In this paper, the objective function of OBDO model is formulated. An example is illustrated to prove the feasibility and practicability of the overall benefit-duration optimization problem. The significance of employing OBDO model and future research work are also described.

• Journal of the Korea Computer Industry Society
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• v.7 no.3
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• pp.191-198
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• 2006

Area of software measurement is active more than thirty years. There is a huge collection of researches but still no concrete software development effort, duration and cost estimation model. The data sets used to conduct previous studies in the duration estimation model are often small and not too recent, these types of models should not be apply in recent projects that have complex architecture and various development environment. Therefore, Oligny et al. presents empirical models that predict software project duration in accordance with project platform based on project effort using the log data transformation. These models are based on the analysis of 396 project data provided by release 4 of the ISBSG Benchmark. Applying Oligny et al.'s models to 534 project data provided release 6 of the ISBSG Benchmark, the project duration is affected by development type more than development platform. Therefore, This paper presents the model of duration estimation according to development type. This paper proves the duration is more affected by development type than development platform. And, The model according to development type is more adequate for duration estimation.

• The KIPS Transactions:PartD
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• v.10D no.7
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• pp.1127-1136
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• 2003

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 models estimate the development effort using the function point that is measured from the requirement specification. This paper presents optimal team size and duration prediction based on function point in order to provide information that can be used as a guide in selecting the most Practical and productive team size for a software development project. We introduce to productive metrics and cost for decision criteria of ideal team size and duration. The experimental is based on the analysis of 300 development and enhancement software project data. These data sets are divide in two subgroups. One is a development project; the other is a maintenance project. As a result of evaluation by productivity and cost measured criteria in two subgroups, we come to the conclusion that the most successful projects has small teams and minimum duration. Also, I proposed that predictive model for team sire and duration according to function point size based on experimental results. The presented models gives a criteria for necessary team site and duration according to the software size.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.1
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• pp.1-11
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• 2017

Stochastic resource-constrained project scheduling problem is an extension of resource-constrained project scheduling problem such that activity duration has stochastic nature. In real situation where activity duration is not known until the activity is finished, open-loop based static policies such as activity-based policy and priority-based policy will not well cope with duration variability. Then, a dynamic policy based on closed-loop decision making will be regarded as an alternative toward achievement of minimal makespan. In this study, a dynamic policy designed to select activities to start at each decision time point is illustrated. The performance of static and dynamic policies based on variable neighborhood search is evaluated under the discrete-event simulation environment. Experiments with J120 sets in PSPLIB and several probability distributions of activity duration show that the dynamic policy is superior to static policies. Even when the variability is high, the dynamic policy provides stable and good solutions.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.397-402
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• 2013

In super-tall building construction projects, schedule risk factors which vertically change and are not found in the low and middle-rise building construction influence duration of a project by vertical attribute; and it makes hard to estimate activity or overall duration of a construction project. However, the existing duration estimating methods, that are based on quantity and productivity assuming activities of the same work item have the same risk and duration regardless of operation space, are not able to consider the schedule risk factors which change by the altitude of operation space. Therefore, in order to advance accuracy of duration estimation of super-tall building projects, the degree of changes of these risk factors according to altitude should be analyzed and incorporated into a duration estimating method. This research proposes a simulation model using Monte Carlo method for estimating activity duration incorporating schedule risk factors by weather conditions in a super-tall building. The research process is as follows. Firstly, the schedule risk factors in super-tall building are identified through literature and expert reviews, and occurrence of non-working days at high altitude by weather condition is identified as one of the critical schedule risk factors. Secondly, a calculating method of the vertical distributions of the weather factors such as temperature and wind speed is analyzed through literature reviews. Then, a probability distribution of the weather factors is developed using the weather database of the past decade. Thirdly, a simulation model and algorithms for estimating non-working days and duration of each activity is developed using Monte-Carlo method. Finally, sensitivity analysis and a case study are carried out for the validation of the proposed model.

• Journal of the military operations research society of Korea
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• v.3 no.1
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• pp.123-136
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• 1977

This thesis presents a modification and extension to the Burgess and Killebrew heuristic resource leveling procedure for project networks. In contrast to previous algorithms appearing in the literature, the objective function of this algorithm. is the minimization of the sum of the squared errors in each time period (deviations around the mean usage) of all resources over the duration of the project. This objective function continues the search for an improved schedule beyond that of previous algorithms with their associated objective functions. One important feature is that the algorithm tends to reduce the number of periods that a resource is idle during its duration on the project.

• Journal of Intelligence and Information Systems
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• v.6 no.2
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• pp.91-98
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• 2000

Despite their wide 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 for project progression. This study proposes a framework for estimation by loaming 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 the due bate and by a certain date. By implementing such customized system, project manager can be aware of changing project status more effectively and better revise resource allocation plans.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.383-387
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• 2003

Construction project has many problem such as delay of the appointed date delivery, over budget, wether and site conditions. When several activities are influenced by the same factor, their duration may be delayed. This paper deals with the problem of construction duration estimating and schedule variation on the construction project. The theory of constraints technique for project management is referred to 'Critical Chain' technique. This paper shows optimal scheduling plan and time management technique, used probability construction duration estimating and scheduling buffer based on the critical chain project management.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.79-86
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• 2020

To make a satisfactory decision regarding project scheduling, a trade-off between the resource-related cost and project duration must be considered. A beneficial method for decision makers is to provide a number of alternative schedules of diverse project duration with minimum resource cost. In view of optimization, the alternative schedules are Pareto sets under multi-objective of project duration and resource cost. Assuming that resource cost is closely related to resource leveling, a heuristic algorithm for resource capacity reduction (HRCR) is developed in this study in order to generate the Pareto sets efficiently. The heuristic is based on the fact that resource leveling can be improved by systematically reducing the resource capacity. Once the reduced resource capacity is given, a schedule with minimum project duration can be obtained by solving a resource-constrained project scheduling problem. In HRCR, VNS (Variable Neighborhood Search) is implemented to solve the resource-constrained project scheduling problem. Extensive experiments to evaluate the HRCR performance are accomplished with standard benchmarking data sets, PSPLIB. Considering 5 resource leveling objective functions, it is shown that HRCR outperforms well-known multi-objective optimization algorithm, SPEA2 (Strength Pareto Evolutionary Algorithm-2), in generating dominant Pareto sets. The number of approximate Pareto optimal also can be extended by modifying weight parameter to reduce resource capacity in HRCR.