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곽한성(Gwak, Han-Seong),손창백(Son, Chang-Back),이동은(Lee, Dong-Eun) 대한건축학회 2012 大韓建築學會論文集 : 構造系 Vol.28 No.10
Task based modeling is essential in a construction operation simulation modeling. It allows dealing with local variables or delay factors that affect productivity and improves the reusability of existing operation models. An operation model can secure reality only if it reflects the real construction processes by effectively dealing with zoning issue. However, system users have some difficulties in modeling a construction operation that is consisted of several processes having different production units. Zoning is a major modeling issue when the task based modeling method is implemented using the existing discrete event simulation systems. This paper highlights the difficulty and presents a new method that complements the zoning issues attributed to different production units. The method is described in detail by presenting the flow of entities. It is confirmed that the zoning method effectively deals with the unbalance of production units between processes and facilitates to model an operation model having processes with different production units. The "Zoning module" contributes to increasing accuracy of simulation result.
곽한성(Gwak, Han-Seong),이창용(Yi, Chang-Yong),이동은(Lee, Dong-Eun) 대한건축학회 2014 大韓建築學會論文集 : 構造系 Vol.30 No.3
Planning earthmoving haul-route must be preceded for appropriate equipment fleet assignment. However, traditional haul-route planning methods have limitations relative to practical usage because multiple variables (e.g., grade/rolling resistance, length, equipment"s weight etc.) should be considered at a time. Genetic algorithm(GA) was introduced to improve these traditional methods. However, GA based haul-route planning method still remains in inefficiency relative to computation performance. This study presents a new haul-route searching method that computes an optimal haul-route using GA. Sensitivity analysis is incorporated in to the system to facilitate finding optimal combination of GA parameters. In addition, simulation is also adopted to improve the reliability of GA experiment. The system prototype is developed by using MATLAB(ver. 2008b). The system identifies an optimal haul-route by considering equipment type, soil type, and soil condition. A case study is presented to demonstrate the system and to verify the validity of the system.
곽한성(Gwak, Han-Seong),배상희(Bea, Sang-Hee),이동은(Lee, Dong-Eun) 대한건축학회 2018 大韓建築學會論文集 : 構造系 Vol.34 No.2
Resource leveling minimizes resource fluctuations by deferring the earliest start times (ESTs) of non-critical activities within their corresponding total float. The intentional float-consumption for resource leveling purpose reduces the schedule delay contingency. This paper presents a method called Genetic Algorithm based Resource Leveling (GARL) that minimizes resource fluctuations and float-consumption impact over project duration. It identifies activities that are less sensitive to float-consumption and performs resource leveling using those activities. The study is of value to project scheduler because GARL identifies the set of activities to be deferred and the number of shift day(s) of each and every activities in the set within its total float expeditiously. It contributes to establish a baseline schedule which implements an optimal resource leveling plan. A case study is presented to verify the validity and usability of the method. It was confirmed that GARL satisfies the project duration constraint by considering resource fluctuations and float-consumption over project duration.
곽한성(Gwak, Han-Seong),서종원(Seo, Jong-Won),이동은(Lee, Dong-Eun) 대한건축학회 2015 大韓建築學會論文集 : 構造系 Vol.31 No.3
This paper presents an Eco haul-route searching method using genetic algorithm(GA), hence minimizing the fuel consumption. It utilizes hourly equipment fuel consumption that change according to their operating conditions classified into three categories, evaluates alternative haul-routes, identifies near optimal solution(s) exhaustively by simultaneously taking into account 3 dimensional contour data, the physical dimensions of equipment, and geological features of the job site surface under study. The method identifies an energy saving haul-route within a job site. It improves usability of existing methods. A case study is presented to demonstrate the system and to validate the system.
곽한성 ( Gwak Han-seong ),최병윤 ( Choi Byung-youn ),이창용 ( Yi Chang-yong ),이동은 ( Lee Dong-eun ) 한국건축시공학회 2018 한국건축시공학회 학술발표대회 논문집 Vol.18 No.1
The accuracy of contingency estimation plays an important role for dealing with the uncertainty of the financial success of construction project. Its’ estimation may be used for various purposes such as schedule control, emergency resolve, and quality expense, etc. This paper presents a contingency estimation method which is schedule control specific. The method 1) implements stochastic EVMS, 2) detects a specific timing for schedule compression, 3) identifies an optimal strategy for shortening planned schedule, 4) finds a probability density function (PDF) of project cost overrun, and 5) estimates the optimal contingency cost based on the level of confidence. The method facilitates expeditious decisions involved in project budgeting. The validity of the method is confirmed by performing test case.
이창용,곽한성,이동은,Yi, Chang-Yong,Gwak, Han-Seong,Lee, Dong-Eun 大韓建築學會 2014 大韓建築學會論文集 : 構造系 Vol.30 No.8
Reducing greenhouse gas(GHG) emissions is a worldwide concern. Low carbon construction is an important operation management goal. Construction resources(i.e., equipment and laborer) are major contributors to producing GHG, and they are the main target for achieving low carbon construction. The amount of Carbon emissions varies depending on the operating conditions. This paper introduces a method which measures the variability of carbon emissions amounts. First, it allows creating construction operation models of which the level of detail is breakdown into the work task level. It makes use of the equipments' hourly fuel consumption and laborers' hourly respiration rate. Second, the method implements sensitivity analysis along with ranges of resources that are allocated in an operation model. It facilitates to find the optimal resource combination using the operation performances such as the amount of emissions, operation completion time, operation completion cost, and productivity. Third, it identifies the best fit probability distribution functions of performance criteria given a certain resource combination. It allows project manager to query the chance to complete the operation within limitations of multiple performance criteria specified by the system users.