• International Journal of Aerospace System Engineering
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• v.2 no.2
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• pp.29-33
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• 2015

The multidisciplinary design optimization (MDO) of a launch vehicle (LV) with a hybrid rocket engine (HRE) was carried out to investigate the ability of an HRE for a single-stage LV. The non-dominated sorting genetic algorithm-II (NSGA-II) was employed to solve two design problems. The design problems were formulated as two-objective cases involving maximization of the downrange distance over the target flight altitude and minimization of the gross weight, for two target altitudes: 50.0 km and 100.0 km. Each objective function was empirically estimated. Several non-dominated solutions were obtained using the NSGA-II for each design problem, and in each case, a trade-off was observed between the two objective functions. The results for the two design problem indicate that economical performance of the LV is limited with the HRE in terms of the maximum downrange distances achievable. The LV geometries determined from the non-dominated solutions were examined.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.292-296
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• 2010

본 연구에서는 상대적으로 소규모 홍수저감시설인 천변저류지의 설치를 통하여 대규모 유역 하도 전체에서의 홍수위 저감효과를 평가하고 그 효율을 극대화 하는 방안을 제시하였다. 본 연구에 적용한 다목적 최적화 기법(Multi-objective Optimization)으로는 NSGA-II(Non-dominated Sorting Genetic Algorithm II) 알고리즘을 적용하였으며 천변저류지 설치에 따른 수위 영향구간 분석 및 유역 전체 하도구간에서 전반적으로 발생하는 수리, 수문학적인 변화 평가 및 천변저류지 최적 조합을 선정하기 위하여 천변저류지의 용량을 최소화하면서 하도 전 구간에서의 수위 저감량을 최대화할 수 있도록 최적화 알고리즘의 목적함수를 설정하였다. 천변저류지 설치에 따른 홍수량의 변화를 해석하기 위하여 안성천 유역에 대하여 동역학적 홍수추적을 수행하였으며 저류형 구조물의 설치에 따른 홍수량 저감효과 및 그에 따른 홍수위의 변화를 동시에 해석하기 위하여 UNET 모형을 기반으로 한 HEC-RAS 부정류 해석을 실시하였다. 천변저류지 조합별로 다양한 경우의 수가 존재하므로 HEC-RAS 구동 모듈인 HECRAS Controller를 Visual Basic으로 코딩된 최적화 알고리즘 프로그램과 연동함으로써 각 경우의 수별로 동역학적 홍수추적 및 부정류 해석을 실시함으로써 천변저류지 조합별 각 측점에서의 홍수량 및 홍수위를 산정하여 저류지 용량을 최소화하면서 각 하도 측점별 수위저감량을 최대화 하는 최적해 집단(Pareto Front)을 산정하여 제시하였다.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.33 no.3
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• pp.225-230
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• 2020

Recently, with the miniaturization of GIS, there is a need for the miniaturization of spacers as accessories. Miniaturized spacers make it difficult to secure adequate insulation distances, resulting in a more concentrated electric field at the triple junction of high-voltage (HV) conductor-insulator (spacer)-insulation gas (SF₆), which is a weakness in GIS. Therefore, by introducing a new concept design technology, functionally graded material (FGM), which is recently applied to various materials and parts industries, three-dimensional control of the dielectric constant distribution in a spacer can be expected to alleviate triple-junction electric field occupancy and improve insulation performance. In this study, we propose an optimized model using NSGA-II to optimize the permittivity distribution of FGM applied spacer.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2177-2193
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• 2018

This paper studies resource allocation schemes for the relay-aided cooperative system consisting of multiple source-destination pairs and decode-forward (DF) relays. Specially, relaying selection, multisubcarrier pairing and assignment, and power allocation are investigated jointly. We consider a combinatorial optimization problem on quality of experience (QoE) and energy consumption based on relay-aided cooperative system. For providing better QoE and lower energy consumption we formulate a multi-objective optimization problem to maximize the total mean opinion score (MOS) value and minimize the total power consumption. To this end, we employ the nondominated sorting genetic algorithm version II (NSGA-II) and obtain sets of Pareto optimal solutions. Specially, two formulas are devised for the optimal solutions of the multi-objective optimization problems with and without a service priority constraint. Moreover, simulation results show that the proposed schemes are superior to the existing ones.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4329-4348
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• 2019

Mobile cloud computing (MCC) can offload heavy computation from mobile devices onto nearby cloudlets or remote cloud to improve the performance as well as to save energy for these devices. Therefore, it is essential to consider how to achieve efficient computation offloading with constraints for multiple users. However, there are few works that aim at multi-objective problem for multiple users. Most existing works concentrate on only single objective optimization or aim to obtain a tradeoff solution for multiple objectives by simply setting weight values. In this paper, a multi-objective optimization model is built to minimize the average energy consumption, time and cost while satisfying the constraint of bandwidth. Furthermore, an improved multi-objective optimization algorithm called D-NSGA-II-ELS is presented to get Pareto solutions with better convergence and diversity. Compared to other existing works, the simulation results show that the proposed algorithm can achieve better performance in terms of energy consumption, time and cost while satisfying the constraint of the bandwidth.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.2
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• pp.125-134
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• 2022

Recently, there are an increased the number of reports on the misuse or malicious use of an UAS. Thus, many researchers are studying on defense schemes for UAS by developing or improving C-UAS sensor technology. However, the wrong placement of sensors may lead to a defense failure since the proper placement of sensors is critical for UAS defense. In this study, a multi-object optimization model for C-UAS sensor placement in an air base is proposed. To address the issue, we define two objective functions: the intersection ratio of interested area and the minimum detection range and try to find the optimized placement of sensors that maximizes the two functions. C-UAS placement model is designed using a NSGA-II algorithm, and through experiments and analyses the possibility of its optimization is verified.

• Transactions of Materials Processing
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• v.32 no.5
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• pp.276-286
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• 2023

The field of sheet metal forming using press technology has become essential in modern mass production systems. Draw bead is often used to enhance formability. However, optimal draw bead design often requires excessive time and cost due to iterative experimentation and sometimes results in some defects. Given these challenges, there is a need to enhance formability by introducing segmented blank holders without draw beads. In this paper, the feasibility of a localized holding strategy using segmented blank holders is evaluated without the use of draw beads. The possibility for improving the formability was evaluated by utilizing a combination of the forming limit diagram and the wrinkle pattern-based defect indicators. Artificial neural networks were used for predicting defect indicators corresponding to arbitrary input holding forces and the NSGA-II optimization algorithm is used to find optimum blank holder forces yielding better defect indicators than the original process with drawbeads. Using optimum holding forces obtained from the proposed procedure, the stamping process with the segmented blank holders can yield better formability than the conventional process with drawbeads.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.29 no.6
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• pp.555-562
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• 2016

Seismic design of braced frames that simultaneously considers economic issues and structural performance represents a rather complicated engineering problem, and therefore, a systematic and well-established methodology is needed. This study proposes a multi-objective seismic design method for an inverted V-braced frame with suspended zipper struts that uses the non-dominated sorting genetic algorithm-II(NSGA-II). The structural weight and the maximum inter-story drift ratio as the objective functions are simultaneously minimized to optimize the cost and seismic performance of the structure. To investigate which of strength- and performance-based design criteria for braced frames is the critical design condition, the constraint conditions on the two design methods are simultaneously considered (i.e. the constraint conditions based on the strength and plastic deformation of members). The linear static analysis method and the nonlinear static analysis method are adopted to check the strength- and plastic deformation-based design constraints, respectively. The proposed optimal method are applied to three- and six-story steel frame examples, and the solutions improved for the considered objective functions were found.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.5
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• pp.535-541
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• 2015

In this study, an approximate multi-objective optimization of a wall-mounted monitor bracket arm was performed. The rotation angle of the bracket arm was determined considering the inplane degree of freedom. We then formulated an optimization problem on maximum stress and deflection. Analyses of mean and design parameters were conducted for sensitivity regarding performance with orthogonal array and response surface method (RSM). RSM models of objective and constraint functions were generated using central composite (CCD) and D-optimal design. The accuracy of approximate models was evaluated through $R^2$ value. The obtained optimal solutions by non-dominant sorting genetic algorithm (NSGA-II) were validated through the finite element analysis and we compared the obtained optimal solution by CCD and D-optimal design.

• The KIPS Transactions:PartB
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• v.11B no.7 s.96
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• pp.841-848
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• 2004

Evolutionary a1gorithms are well-suited for multi-objective optimization problems involving several, often conflicting objectives. Pareto-based evolutionary algorithms, in particular, have shown better performance than other multi-objective evolutionary algorithms in comparison. However, generalized evolutionary multi-objective optimization algorithms have a weak point, in which the distribution of solutions are not uni-formly distributed onto Pareto optimal front. In this paper, we propose an evolutionary a1gorithm for multi-objective optimization which uses seed individuals in order to overcome weakness of algorithms Published. Seed individual means a solution which is not located in the crowded region on Pareto front. And the idea of our algorithm uses seed individuals for reproducing individuals for next generation. Thus, proposed a1go-rithm takes advantage of local searching effect because new individuals are produced near the seed individual with high probability, and is able to produce comparatively uniform distributed pareto optimal solutions. Simulation results on five testbed problems show that the proposed algo-rithm could produce uniform distributed solutions onto pareto optimal front, and is able to show better convergence compared to NSGA-II on all testbed problems except multi-modal problem.