• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.447-448
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• 2013

• Smart Structures and Systems
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• v.14 no.1
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• pp.55-70
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• 2014

The paper presents a multi-objective optimization strategy for a multi-type sensor placement for Structural Health Monitoring (SHM) of long span bridges. The problem is formulated for simultaneous placement of strain sensors and accelerometers (heterogeneous network) based on application demands for SHM system. Modal Identification (MI) and Accurate Mode Shape Expansion (AMSE) were chosen as the application demands for SHM. The optimization problem is solved through the use of integer Genetic Algorithm (GA) to maximize a common metric to ensure adequate MI and AMSE. The performance of the joint optimization problem solved by GA is compared with other established methods for homogenous sensor placement. The results indicate that the use of a multi-type sensor system can improve the quality of SHM. It has also been demonstrated that use of GA improves the overall quality of the sensor placement compared to other methods for optimization of sensor placement.

• Industrial Engineering and Management Systems
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• v.11 no.2
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• pp.155-164
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• 2012

As the global market becomes more competitive, manufacturing industries face relentless pressure caused by a growing tendency of greater varieties of products, shorter manufacturing cycles and more sophisticated customer requirements. Efficient and effective supplier selection and order allocation decisions are, therefore, important decisions for a manufacturer to ensure stable material flows in a highly competitive supply chain, in particular, when customers are willing to accept products with less desirable product attributes (e.g., color, delivery date) for economic reasons. This paper attempts to solve optimally the challenging problem of supplier selection and order allocation, taking into consideration the customer flexibility for a manufacturer producing multi-products to satisfy the customers' demands in a multi period planning horizon. A new mixed integer programming model is developed to describe the behavior of the supply chain. The objective is to maximize the manufacturer's total profit subject to various operating constraints of the supply chain. Due to the complexity and non-deterministic polynomial-time (NP)-hard nature of the problem, an improved genetic approach is proposed to solve the problem optimally. This approach differs from a canonical genetic algorithm in three aspects: a new selection method to reduce the chance of premature convergence and two problem-specific repair heuristics to guarantee feasibility of the solutions. The results of applying the proposed approach to solve a set of randomly generated test problems clearly demonstrate its excellent performance. When compared with applying the canonical genetic algorithm to locate optimal solutions, the average improvement in the solution quality amounts to as high as ten percent.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.233-235
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• 2000

SVC(Static Var Compensator) is commonly installed with conventional mechanically switched existing reactor or capacitor banks for wide range voltage control. The frequencies of switching of external banks have a great impact on the quality of voltage, but is limited since the life time of the external banks depends severely on the number of switching. So it is a complete multi-objective nonlinear optimization problem with conflicting objectives. This paper presents a method to determine the optimal coordination of SVC and external banks using genetic algorithm based on the multi-objective criteria. Optimal dead band and delay time of external banks is sought for reliable and efficient operation

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.04a
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• pp.245-253
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• 1998

Recently, the importance of multi-objective optimization techniques and stochastic search methods is increasing. The stochastic search methods have the concepts of the survival of the fittest and natural selection such as genetic algorithms(GA), simulated annealing(SA) and evolution strategies (ES). As many accidents of oil tankers cause marine pollution, oil tankers of double hull or mid deck structure are being built to minimize the marine pollution. For the improvement of oil tanker design technique, an efficient optimization technique is proposed in this study. Multi-objective optimization problem of weight and cost of double hull and mid deck tanker is formulated. Discrete design variables are used considering real manufacturing, and the concept of relative production cost is also introduced. The ES method is used as an optimization technique, and the ES algorithm was developed to generate a more efficient Pareto optimal set.

• Journal of Ocean Engineering and Technology
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• v.28 no.5
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• pp.404-410
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• 2014

The purpose of this study was to find the optimal arrangement of FPSO equipment in a module while considering the economic value and fire risk. We estimated the economic value using the pipe connections and pump installation cost in an HP (high pressure) gas compression module. The equipment risks were also analyzed using fire scenarios based on historical data. To consider the wind effect during a fire accident, fuzzy modeling was applied to improve the accuracy of the analysis. The objective functions consisted of the economic value and fire risk, and the constraints were the equipment maintenance and weight balance of the module. We generated a Pareto-optimal front group using a multi-objective GA (genetic algorithm) and suggested an equipment arrangement method that included the opinions of the designer.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.19 no.7
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• pp.500-511
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• 2007

The Optimal solutions of the design variables in internally finned tubes have been obtained for three-dimensional periodically fully developed turbulent flow and heat transfer. For a trapezoidal fin profile, performances of the heat exchanger are determined by considering the heat transfer rate and pressure drop, simultaneously, that are interdependent quantities. Therefore, Pareto frontier sets of a heat exchanger can be acquired by integrating CFD and a multi-objective optimization technique. The optimal values of fin widths $(d_1,\;d_2)$, fin height(h) and helix angle$(\gamma)$ are numerical1y obtained by minimizing the pressure loss and maximizing the heat transfer rate within ranges of $d_1=0.5\sim1.5mm$, $d_2=0.5\sim1.5mm$, $h=0.5\sim1.5mm$, and $\gamma=0\sim20^{\circ}$. For this, a general CFD code and a global genetic algorithm(GA) are used. The Pareto sets of the optimal solutions can be acquired after $30^{th}$ generation.

• Korean Management Science Review
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• v.29 no.2
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• pp.21-34
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• 2012

This paper addresses a network design problem in a supply chain system that involves locating both plants and distribution centers, and determining the best strategy for distributing products from the suppliers to the plants, from the plants to the distribution centers and from the distribution centers to the customers. This paper suggests a cooperative coevolutionary algorithm (CCEA) approach to solve the model. First, the problem is decomposed into three subproblems for each of which the chromosome population is created correspondingly. Each chromosome in each population is represented as a permutation denoting the priority. Then an algorithm generating a solution from the combined set of chromosomes from each population is suggested. Also an algorithm evaluating the performance of a solution is suggested. An experimental study is carried out. The results show that our CCEA tends to generate better solutions than the previous CCEA as the problem size gets larger and that the permutation representation for chromosome used here is better than other representation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.462-465
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• 2002

This paper deals with the problem of synthesis of stable and optimal grasps with unknown objects by 3-finger hand. Previous robot grasp research has analyzed mainly with either unknown objects 2D by vision sensor or unknown objects, cylindrical or hexahedral objects, 3D. Extending the previous work, in this paper we propose an algorithm to analyze grasp of unknown objects 3D by vision sensor. This is archived by two steps. The first step is to make a 3D geometrical model of unknown objects by stereo matching which is a kind of 3D computer vision technique. The second step is to find the optimal grasping points. In this step, we choose the 3-finger hand because it has the characteristic of multi-finger hand and is easy to modeling. To find the optimal grasping points, genetic algorithm is used and objective function minimizing admissible farce of finger tip applied to the object is formulated. The algorithm is verified by computer simulation by which an optimal grasping points of known objects with different angles are checked.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.11
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• pp.54-64
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• 2002

This paper deals with the problem of synthesis of stable and optimal grasps with unknown objects by 3-finger hand. Previous robot grasp research has mainly analyzed with either unknown objects 2-dimensionally by vision sensor or known objects, such as cylindrical objects, 3-dimensionally. As extending the previous work, in this study we propose an algorithm to analyze grasp of unknown objects 3-dimensionally by using vision sensor. This is archived by two steps. The first step is to make a 3-dimensional geometrical model for unknown objects by using stereo matching. The second step is to find the optimal grasping points. In this step, we choose the 3-finger hand which has the characteristic of multi-finger hand and is easy to model. To find the optimal grasping points, genetic algorithm is employed and objective function minimizes the admissible force of finger tip applied to the objects. The algorithm is verified by computer simulation by which optimal grasping points of known objects with different angle are checked.