• Journal of Ocean Engineering and Technology
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• v.17 no.6
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• pp.23-31
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• 2003

As there are so many uncertainties associated with using the determinism analysis method in the design of rubble mound breakwater, it is impossible for a designed construction to provide ultimate stability. First of all, due to the uncertainty of Load and Resistance, a safety level concerning the destruction mode of construction must be given. Then, the optimization design should be processed. After all, we can say that it is a more reasonable design method than the design used by the stability rate. In this study, an established design process is accomplished using Hudson's equation and an economic analysis with the breakwater's section is also conducted. Hudson's equation is compared to Van der Meer's equation. These results are utilized to drop a damage rate, increase the stability of construction, and determine the optimization section of the breakwater.

• Journal of the Korean Society for Railway
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• v.2 no.3
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• pp.9-17
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• 1999

This paper presents a new algorithm to determine the pre-loads that sustain the static equilibrium state in a given position. The algorithm which uses a partial velocity matrix leads to an unconstrained optimization problem to compute the pre-loads of the suspensions. To demonstrate the validity of the proposed algorithm, the static analysis results that employ the pre-loads of three examples are presented using a reliable commercial program. Results of the analysis confirm the validity of the proposed algorithm.

• Journal of Electrical Engineering and Technology
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• v.5 no.1
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• pp.45-53
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• 2010

This paper presents an improved parallel particle swarm optimization approach (IPPSO) based decomposed network for economic power dispatch with discontinuous fuel cost functions. The range of partial power demand corresponding to the partial output powers near the global optimal solution is determined by a flexible decomposed network strategy and then the final optimal solution is obtained by parallel Particle Swarm Optimization. The proposed approach tested on 6 generating units with smooth cost function, and to 26-bus (6 generating units) with consideration of prohibited zone effect, the simulation results compared with recent global optimization methods (Bee-OPF, GA, MTS, SA, PSO). From the different case studies, it is observed that the proposed approach provides qualitative solution with less computational time compared to various methods available in the literature survey.

• Journal of applied mathematics & informatics
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• v.7 no.2
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• pp.453-465
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• 2000

In this paper, a new method for finding the approximate solution of a second order nonlinear partial differential equation is introduced. In this method the problem is transformed to an equivalent optimization problem. them , by considering it as a distributed parameter control system the theory of measure is used for obtaining the approximate solution of the original problem.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.22 no.3
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• pp.191-201
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• 2010

The breakwaters are designed by considering the cost optimization because a human risk is seldom considered. Most breakwaters, however, were constructed without considering the cost optimization. In this study, the optimum return period, target failure probability and the partial safety factors were evaluated by applying the cost optimization to the rubble mound breakwaters in Korea. The applied method was developed by Hans F. Burcharth and John D. Sorensen in relation to the PIANC Working Group 47. The optimum return period was determined as 50 years in many cases and was found as 100 years in the case of high real interest rate. Target failure probability was suggested by using the probabilities of failure corresponding to the optimum return period and those of reliability analysis of existing structures. The final target failure probability is about 60% for the initial limit state of the national design standard and then the overall safety factor is calculated as 1.09. It is required that the nominal diameter and weight of armor are respectively 9% and 30% larger than those of the existing design method. Moreover, partial safety factors considering the cost optimization were compared with those calculated by Level 2 analysis and a fairly good agreement was found between the two methods especially the failure probability less than 40%.

• 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.

• Communications of the Korean Mathematical Society
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• v.13 no.1
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• pp.195-209
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• 1998

In this paper we present a new iteration method for solving optimization problems governed by partial differential equations. We generalize the existing methods such as simple gradient methods and pseudo-time methods to get an efficient iteration method. Numerical tests show that the convergence of the new iteration method is much faster than those of the pseudo-time methods especially when the parameter $\sigma$ in the cost functional is small.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.377-382
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• 2004

This paper presents a novel optimization method for the air- and gas-supplying network comprised of several air compression systems and air and gas streams in an industrial chemical plant. The optimization is based on the hybrid model developed by Han and $Han^1$ for predicting the power consumption of a compression system. A constrained optimization problem was formulated to minimize the total electric power consumption of all the compression systems in the air- and gas-supplying network under various operating constraints and was solved using a successive quadratic optimization algorithm. The optimization approach was applied to an industrial terephthalic acid manufacturing plant to achieve about 10% reduction in the total electric power consumption under varying ambient conditions.

• Journal of the Korea Society of Computer and Information
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• v.20 no.12
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• pp.75-82
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• 2015

Generally, the optimal solution of assignment problem can be obtained by Hungarian algorithm of two-sided optimization with time complexity $O(n^4)$. This paper suggests one-sided optimal assignment and swap optimization algorithm with time complexity $O(n^2)$ can be achieve the goal of two-sided optimization. This algorithm selects the minimum cost for each row, and reassigns over-assigned to under-assigned cell. Next, that verifies the existence of swap optimization candidates, and swap optimizes with ${\kappa}-opt({\kappa}=2,3)$. For 27 experimental data, the swap-optimization performs only 22% of data, and 78% of data can be get the two-sided optimal result through one-sided optimal result. Also, that can be improves on the solution of best known solution for partial problems.

• Journal of the Society of Naval Architects of Korea
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• v.45 no.6
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• pp.590-600
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• 2008

This paper concerns the development of a designer friendly hull form parameterization and its coupling with advanced global optimization algorithms. As optimization algorithms, we choose the Partial Swarm Optimization(PSO) recently introduced to solve global optimization problems. Most general-purpose optimization softwares used in industrial applications use gradient-based algorithms, mainly due to their convergence properties and computational efficiency when a relatively few number of variables are considered. However, local optimizers have difficulties with local minima and non-connected feasible regions. Because of the increase of computer power and of the development of efficient Global Optimization (GO) methods, in recent years nongradient-based algorithms have attracted much attention. Furthermore, GO methods provide several advantages over local approaches. In the paper, the derivative-based SQP and the GO approach PSO are compared with their relative performances in solving some typical ship design optimization problem focusing on their effectiveness and efficiency.