• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.04a
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• pp.200-201
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• 2022

Off-Site Construction is being widely adopted as an alternative to solve endemic problems in construction industry such as low productivity and efficiency. However, it is strongly recommended to examine the transportation process to be optimized because it determines the size of a modular and influences the cost of the construction. Therefore, in this study simulation model for optimization of modular construction transportation plan was developed using AnyLogic. As a result of the study, the influence of trailer transport capacity and transport time increases as the number of modular which should be transported from factory to site increases.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.195-204
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• 2003

Network optimization is being increasingly important and fundamental issue in the fields such as engineering, computer science, operations research, transportation, telecommunication, decision support systems, manufacturing, and airline scheduling. Networks provide a useful way to modeling real world problems and are extensively used in practice. Many real world applications impose on more complex issues, such as, complex structure, complex constraints, and multiple objects to be handled simultaneously and make the problem intractable to the traditional approaches. Recent advances in evolutionary computation have made it possible to solve such practical network optimization problems. The invited talk introduces a thorough treatment of evolutionary approaches, i.e., hybrid genetic algorithms approach to network optimization problems, such as, fixed charge transportation problem, minimum cost and maximum flow problem, minimum spanning tree problem, multiple project scheduling problems, scheduling problem in FMS.

• Journal of Forest and Environmental Science
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• v.32 no.2
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• pp.173-181
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• 2016

This study designed a model of the efficient production schemes and raw materials transportation optimization of current South Korean's simple and monolithic distribution system of wood to build a SCM (supply chain management) as a basic level to establish a distribution of future by pellet production of raw materials costs and reduce transport costs, and specifically to forest of pallet to contribute to revitalizing the market. The result of each transportation costs after building the best transportation network from raw material supply area to demand area applying transport law was 964,600 thousands Won from 6 supply areas to 7 demand areas. And the result of each model's analysis to get the pellet's efficient production through production cost reduction showed that it reduced from 325,701 Won/t to 240,106 Won/t, results of existing efficient pellet for the production model 8,233 tons over 20,000 tons annual production capacity from the size of the expanded production capacity when the expansion. However, when the production size expanded to 50,000 Tons of the production, the effect was very small even though production cost decreased.

• Steel and Composite Structures
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• v.21 no.3
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• pp.501-515
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• 2016

Seismic analysis for steel frame structure with brace configuration using topology optimization based on truss-like material model is studied. The initial design domain for topology optimization is determined according to original steel frame structure and filled with truss-like members. Hence the initial truss-like continuum is established. The densities and orientation of truss-like members at any point are taken as design variables in finite element analysis. The topology optimization problem of least-weight truss-like continuum with stress constraints is solved. The orientations and densities of members in truss-like continuum are optimized and updated by fully-stressed criterion in every iteration. The optimized truss-like continuum is founded after finite element analysis is finished. The optimal bracing system is established based on optimized truss-like continuum without numerical instability. Seismic performance for steel frame structures is derived using dynamic time-history analysis. A numerical example shows the advantage for frame structures with brace configuration using topology optimization in seismic performance.

• Journal of Distribution Science
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• v.14 no.2
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• pp.41-45
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• 2016

Purpose - Finding an optimal path is an essential component for the design and operation of smart transportation or logistics network. Many applications in navigation system assume that travel time of each link is fixed and same. However, in practice, the travel time of each link changes over time. In this paper, we introduce a new transportation problem to find a latest departing time and delivery path between the two nodes, while not violating the appointed time at the destination node. Research design, data, and methodology - To solve the problem, we suggest a mathematical model based on network optimization theory and a backward search method to find an optimal solution. Results - First, we introduce a dynamic transportation problem which is different with traditional shortest path or minimum cost path. Second, we propose an algorithm solution based on backward search to solve the problem in a large-sized network. Conclusions - We proposed a new transportation problem which is different with traditional shortest path or minimum cost path. We analyzed the problem under the conditions that travel time is changing, and proposed an algorithm to solve them. Extending our models for visiting two or more destinations is one of the further research topics.

• Structural Engineering and Mechanics
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• v.85 no.5
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• pp.607-620
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• 2023

The classical optimal control (COC) method has been widely used for linear quadratic regulator (LQR) problems of structural control. However, the equation of motion of the structure is incorporated into the optimization model as the constraint condition for the LQR problem, which needs to be solved through the Riccati equation under certain assumptions. In this study, an explicit optimal control (EOC) method is proposed based on the explicit time-domain method (ETDM). By use of the explicit formulation of structural responses, the LQR problem with the constraint of equation of motion can be transformed into an unconstrained optimization problem, and therefore the control law can be derived directly without solving the Riccati equation. To further optimize the weighting parameters adopted in the control law using the gradient-based optimization algorithm, the sensitivities of structural responses and control forces with respect to the weighting parameters are derived analytically based on the explicit expressions of dynamic responses of the controlled structure. Two numerical examples are investigated to demonstrate the feasibility of the EOC method and the optimization scheme for weighting parameters involved in the control law.

• Nuclear Engineering and Technology
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• v.53 no.11
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• pp.3860-3860
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• 2021

• Journal of Korean Society of Transportation
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• v.20 no.2
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• pp.185-185
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• 2002

• Proceedings of the Korea Port Economic Association Conference
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• 2007.10a
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• pp.161-173
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• 2007

This paper considers the problem of determining the cargo flow and the transportation mode in each trade route while satisfying the demand. Especially, the problem incorporates short sea shipping in Korea, which is becoming more important in order to improve efficiency of Logistics. The objective is to minimize the sum of shipping and inland transportation costs. To solve optimally the problem, this paper employs a linear programming model, which is an operations research technique for optimization. The problem is formulated by extending the well-known network design problem by considering capacity at seaport and limitation of total number of vehicles. The model is solved using CPLEX, a commercial linear program software. The test results using a real cargo flow data in Korea show that the model represents closely the real situation.

• Geomechanics and Engineering
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• v.36 no.3
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• pp.259-276
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• 2024

The undrained shear strength is widely acknowledged as a fundamental mechanical property of soil and is considered a critical engineering parameter. In recent years, researchers have employed various methodologies to evaluate the shear strength of soil under undrained conditions. These methods encompass both numerical analyses and empirical techniques, such as the cone penetration test (CPT), to gain insights into the properties and behavior of soil. However, several of these methods rely on correlation assumptions, which can lead to inconsistent accuracy and precision. The study involved the development of innovative methods using extreme gradient boosting (XGB) to predict the pile set-up component "A" based on two distinct data sets. The first data set includes average modified cone point bearing capacity (q_t), average wall friction (f_s), and effective vertical stress (σ_vo), while the second data set comprises plasticity index (PI), soil undrained shear cohesion (S_u), and the over consolidation ratio (OCR). These data sets were utilized to develop XGBoost-based methods for predicting the pile set-up component "A". To optimize the internal hyperparameters of the XGBoost model, four optimization algorithms were employed: Particle Swarm Optimization (PSO), Social Spider Optimization (SSO), Arithmetic Optimization Algorithm (AOA), and Sine Cosine Optimization Algorithm (SCOA). The results from the first data set indicate that the XGBoost model optimized using the Arithmetic Optimization Algorithm (XGB - AOA) achieved the highest accuracy, with R2 values of 0.9962 for the training part and 0.9807 for the testing part. The performance of the developed models was further evaluated using the RMSE, MAE, and VAF indices. The results revealed that the XGBoost model optimized using XGBoost - AOA outperformed other models in terms of accuracy, with RMSE, MAE, and VAF values of 0.0078, 0.0015, and 99.6189 for the training part and 0.0141, 0.0112, and 98.0394 for the testing part, respectively. These findings suggest that XGBoost - AOA is the most accurate model for predicting the pile set-up component.