• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2006.03a
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• pp.316-323
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• 2006

The main objective of this study was to derive a formula of ductility reduction factor, expressed as $R{\mu}$. To attain this objective, a study comprised reduction factors computed for stiffness degrading systems undergoing different levels of ductility and to investigate an accuracy of the formula. Based on this study, the main conclusions can be summarized :(1) The ductility reduction factor is primarily affected by the period of the system and the displacement ductility ratio. (2) The proposed formula is simpler and the inelastic deformations of bridge structures are better than those by the others formulas we used before.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.407-416
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• 2007

The construction industry in South Korea is experiencing great changes: it is becoming developed on a larger scale, specialized to a high degree and rapidly incorporating with other industries. This development has resulted in higher demand of construction industry. Accordingly, the transparency and an objective method of evaluation in the process of projects in the construction industry are gaining more importance. Clients' and customers' needs also require more specific objective evaluation to find whether their projects are successfully performed or not. This study aims to discuss problems on the current post-evaluation items including the qualitative item analysis such as customer satisfaction. Moreover, this paper suggests the improved ways in which enable the application of the effective evaluation system to the construction industry.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.4
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• pp.55-67
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• 2018

The objective of this study is to investigate the effect of ERP system quality factors on the system use satisfaction and on personal and organizational performances. For achieving this objective, we investigated the interrelationship among quality factors, use satisfaction and business performance in the companies which operate the ERP system using questionnaires, whereas many previous studies focused on general quality factors such as the relationship between system quality and use satisfaction on organizational performance. The difference between our study and previous studies is that we classified the information system quality into three categories (system quality, information quality, and service quality) before analyzing the respective relationship among three identified variables (use satisfaction, individual performance and organization performance). The result of this study proved that the system quality, information quality, and service quality considered as the ERP system quality factors have a positive effect on user satisfaction level, respectively.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.591-595
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• 2010

Conventional methods of model evaluation usually rely only on model performance based on a comparison of simulated variables to corresponding observations. However, this type of model evaluation has been criticized because of its insufficient consideration of the various uncertainty sources involved in modeling processes. This study aims to propose an extended model evaluation method using multiple assesment indices (MAIs) that consider not only the model performance but also the model structure and parameter uncertainties in rainfall-runoff modeling. A simple reservoir model (SFM) and distributed kinematic wave models (KWMSS1 and KWMSS2 using topography from 250m, 500m, and 1km digital elevation models) were developed and assessed by three MAIs for model performance, model structural stability, and parameter identifiability. All the models provided acceptable performance in terms of a global response, but the simpler SFM and KWMSS1 could not accurately represent the local behaviors of hydrographs. In addition, SFM and KWMSS1 were structurally unstable; their performance was sensitive to the applied objective functions. On the other hand, the most sophisticated model, KWMSS2, performed well, satisfying both global and local behaviors. KMSS2 also showed good structural stability, reproducing hydrographs regardless of the applied objective functions; however, superior parameter identifiability was not guaranteed. Numerous parameter sets could lead to indistinguishable hydrographs. This result supports that while making a model complex increases its performance accuracy and reduces its structural uncertainty, the model is likely to suffer from parameter uncertainty. The proposed model evaluation process can provide an effective guideline for identifying a reliable hydrologic model.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2009.04a
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• pp.284-287
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• 2009

In order to plan and manage public facilities effectively and efficiently, it is necessary to diagnose the current status of facilities and decide the objective features. Performance measurement is to provide managers with the information they need to measure competitive advantages. This paper discusses public facility performance in order to establish the conceptual framework for performance measurement for public facilities. In order to develop the measurement of public facility performance, a pilot study was conducted with facilities managers of facilities management corporation of public districts in Seoul. We investigated how public facilities management teams have assessed their performance and collected data regarding financial aspects, service aspects, community aspects, and building aspects. There is no standard format to measure facility performance since building sizes, programs, community needs widely differ. However, it is necessary to have a more consistent system to measure facility performance. In addition, each public municipal district needs to empower each district facilities management corporation to participate in managerial decisions and budget control.

• Korean Journal of Construction Engineering and Management
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• v.5 no.4 s.20
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• pp.79-86
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• 2004

One of the most difficult tasks in pavement management information systems is establishing the links between performance measures of a structure and the design and construction inputs. In-situ pavement performance can be considered a response variable to many project input variables, such as design, construction, and traffic loading effects. If we are to fully understand the component of pavement performance and specify the inputs through design and construction specifications to achieve that performance we must develop quantitative relationship between input and response variables through a scientific, fully integrated Pavement Performance Analysis System (PPAS). Hence, the objective of this study is to design a database model required for developing an effective database template that will allow analysis of pavement performance measures based on design and construction information linked by location. In order to select the most appropriate database model, a conceptual database model (Entity Relationship Model) and dimensional model, which is believed to be the most effective modeling technique for data warehouse project, are designed and compared. It is believed that other state highway agencies could adopt the proposed design strategy for implementing a PPAS at the discretion of the state highway agencies.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.1
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• pp.77-91
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• 2007

In this paper, we present a symbiotic evolutionary algorithm for multi-objective optimization. The goal in multi-objective evolutionary algorithms (MOEAs) is to find a set of well-distributed solutions close to the true Pareto optimal solutions. Most of the existing MOEAs operate one population that consists of individuals representing the entire solution to the problem. The proposed algorithm has a two-leveled structure. The structure is intended to improve the capability of searching diverse and food solutions. At the lower level there exist several populations, each of which represents a partial solution to the entire problem, and at the upper level there is one population whose individuals represent the entire solutions to the problem. The parallel search with partial solutions at the lower level and the Integrated search with entire solutions at the upper level are carried out simultaneously. The performance of the proposed algorithm is compared with those of the existing algorithms in terms of convergence and diversity. The optimization problems with continuous variables and discrete variables are used as test-bed problems. The experimental results confirm the effectiveness of the proposed algorithm.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.113-116
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• 2008

This work presents numerical optimization for design of staggered arrays of dimples printed on opposite surfaces of a cooling channel with a fast and elitist Non-Dominated Sorting of Genetic Algorithm (NSGA-II) of multi-objective optimization. As Pareto optimal front produces a set of optimal solutions, the trends of objective functions with design variables are predicted by hybrid multi-objective evolutionary algorithm. The problem is defined by three non-dimensional geometric design variables composed of dimpled channel height, dimple print diameter, dimple spacing and dimple depth to maximize heat transfer rate compromising with pressure drop. Twenty designs generated by Latin hypercube sampling were evaluated by Reynolds-averaged Navier-Stokes solver and the evaluated objectives were used to construct Pareto optimal front through hybrid multi-objective evolutionary algorithm. The optimum designs were grouped by k-mean clustering technique and some of the clustered points were evaluated by flow analysis. With increase in dimple depth, heat transfer rate increases and at the same time pressure drop also increases, while opposite behavior is obtained for the dimple spacing. The heat transfer performance is related to the vertical motion of the flow and the reattachment length in the dimple.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.4 s.193
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• pp.84-92
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• 2007

Dynamic process planning requires not only more flexible capabilities of a CAPP system but also higher utility of the generated process plans. In order to meet the requirements, this paper develops an algorithm that can select machines for the machining operations by calculating the machine loads. The developed algorithm is based on the multi-objective genetic algorithm that gives rise to a set of optimal solutions (in general, known as the Pareto-optimal solutions). The objective is to satisfy both the minimization number of part movements and the maximization of machine utilization. The algorithm is characterized by a new and efficient method for nondominated sorting through K-means algorithm, which can speed up the running time, as well as a method of two stages for genetic operations, which can maintain a diverse set of solutions. The performance of the algorithm is evaluated by comparing with another multiple objective genetic algorithm, called NSGA-II and branch and bound algorithm.

• Industrial Engineering and Management Systems
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• v.12 no.2
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• pp.151-160
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• 2013

In the past decades, several algorithms based on evolutionary approaches have been proposed for solving job shop scheduling problems (JSP), which is well-known as one of the most difficult combinatorial optimization problems. Most of them have concentrated on finding optimal solutions of a single objective, i.e., makespan, or total weighted tardiness. However, real-world scheduling problems generally involve multiple objectives which must be considered simultaneously. This paper proposes an efficient particle swarm optimization based approach to find a Pareto front for multi-objective JSP. The objective is to simultaneously minimize makespan and total tardiness of jobs. The proposed algorithm employs an Elite group to store the updated non-dominated solutions found by the whole swarm and utilizes those solutions as the guidance for particle movement. A single swarm with a mixture of four groups of particles with different movement strategies is adopted to search for Pareto solutions. The performance of the proposed method is evaluated on a set of benchmark problems and compared with the results from the existing algorithms. The experimental results demonstrate that the proposed algorithm is capable of providing a set of diverse and high-quality non-dominated solutions.