• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.2
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• pp.211-216
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• 2015

Recently, because of the growth in the leisure industry and interest in health, the demand for bicycles has increased. In this research, considering the vertical load on a bike frame under static state conditions, the deflection and mass of the bike frame were minimized by satisfying the service condition and performing optimization. The thickness of the bicycle-frame tube was set to a design variable, and its sensitivity was confirmed by an analysis of means (ANOM). To optimize the solution, a response-surface-method (RSM) model was constructed using D-Optimal and central composite design(CCD). The optimization was performed using a non-dominant sorting genetic algorithm (NSGA-II), and the optimal solution was verified by finite-element analysis.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.2
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• pp.192-197
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• 2015

In many fields, the importance of reducing weight is increasing. A product should be designed such that it is profitable, by lowering costs and exhibiting better performance than other similar products. In this study, the mass and deflection of steel structures have to be reduced as objective functions under constraint conditions. To reduce computational analysis time, central composite design(CCD) and D-Optimal are used in design of experiments(DOE). The accuracy of approximate models is evaluated using the $R^2$ value. In this study, the objective functions are multiple, so the non-dominant sorting genetic algorithm(NSGA-II), which is highly efficient, is used for such a problem. In order to verify the validity of Pareto solutions, CAE results and Pareto solutions are compared.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.8
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• pp.689-696
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• 2014

This paper presents a scheduling problem for a high-density robotic workcell using multi-objective genetic algorithm. We propose a new algorithm based on NSGA-II(Non-dominated Sorting Algorithm-II) which is the most popular algorithm to solve multi-objective optimization problems. To solve the problem efficiently, the proposed algorithm divides the problem into two processes: clustering and scheduling. In clustering process, we focus on multi-robot positions because they are fixed in manufacturing system and have a great effect on task distribution. We test the algorithm by changing multi-robot positions and compare it to previous work. Test results shows that the proposed algorithm is effective under various conditions.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.4
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• pp.439-449
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• 2018

In this paper, multi-objective optimization of a multi-bubble pressure cabin in the underwater glider with Blended-Wing-Body (BWB) is carried out using Kriging and the Non-dominated Sorting Genetic Algorithm (NSGA-II). Two objective functions are considered: buoyancy-weight ratio and internal volume. Multi-bubble pressure cabin has a strong compressive capacity, and makes full use of the fuselage space. Parametric modeling of the multi-bubble pressure cabin structure is automatic generated using UG secondary development. Finite Element Analysis (FEA) is employed to study the structural performance using the commercial software ANSYS. The weight of the primary structure is determined from the volume of the Finite Element Structure (FES). The stress limit is taken into account as the constraint condition. Finally, Technique for Ordering Preferences by Similarity to Ideal Solution (TOPSIS) method is used to find some trade-off optimum design points from all non-dominated optimum design points represented by the Pareto fronts. The best solution is compared with the initial design results to prove the efficiency and applicability of this optimization method.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.248-256
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• 2021

Now that we're in the big data era, data has taken on a new significance as the storage capacity has exploded from trillion bytes to petabytes at breakneck pace. As the use of cloud computing expands and becomes more commonly accepted, several businesses and institutions are opting to store their requests and data there. Cloud storage's concept of a nearly infinite storage resource pool makes data storage and access scalable and readily available. The majority of them, on the other hand, favour a single cloud because of the simplicity and inexpensive storage costs it offers in the near run. Cloud-based data storage, on the other hand, has concerns such as vendor lock-in, privacy leakage and unavailability. With geographically dispersed cloud storage providers, multicloud storage can alleviate these dangers. One of the key challenges in this storage system is to arrange user data in a cost-effective and high-availability manner. A multicloud storage architecture is given in this study. Next, a multi-objective optimization problem is defined to minimise total costs and maximise data availability at the same time, which can be solved using a technique based on the non-dominated sorting genetic algorithm II (NSGA-II) and obtain a set of non-dominated solutions known as the Pareto-optimal set.. When consumers can't pick from the Pareto-optimal set directly, a method based on Principal Component Analysis (PCA) is presented to find the best answer. To sum it all up, thorough tests based on a variety of real-world cloud storage scenarios have proven that the proposed method performs as expected.

• Industrial Engineering and Management Systems
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• v.15 no.4
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• pp.374-384
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• 2016

The efficiency of a supply chain can be extremely affected by its design which includes determining the flow pattern of material from suppliers to costumers, selecting the suppliers, and defining the opened facilities in network. In this paper, a multi-objective multi-echelon multi-product supply chain design model is proposed in which several suppliers, several manufacturers, several distribution centers as different stages of supply chain cooperate with each other to satisfy various costumers' demands. The multi-objectives of this model which considered simultaneously are 1-minimize the total cost of supply chain including production cost, transportation cost, shortage cost, and costs of opening a facility, 2-minimize the transportation time from suppliers to costumers, and 3-maximize the service level of the system by minimizing the maximum level of shortages. To configure this model a graph theoretic approach is used by considering channels among each two facilities as links and each facility as the nodes in this configuration. Based on complexity of the proposed model a multi-objective Pareto-based vibration damping optimization (VDO) algorithm is applied to solve the model and finally non-dominated sorting genetic algorithm (NSGA-II) is also applied to evaluate the performance of MOVDO. The results indicated the effectiveness of the proposed MOVDO to solve the model.

• Proceedings of the KIPE Conference
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• 2012.07a
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• pp.351-352
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• 2012

본 논문에서는 최근 직류송전용 컨버터로 많은 관심이 집중되고 있는 MMC(Modular Multi-level Converter)에 대해서 소개하고 있다. 대용량 전압원 컨버터로 MMC가 적합한 이유에 대해서 설명하고, MMC의 동작원리, SM(Sub-Module) dc capacitor voltage balancing 기술, 전체 제어 시스템에 대해 자세하게 설명하고 있다. 제안하는 MMC는 Staircase Modulation 방식으로 사인파형에 가까운 출력전압을 형성하고, Sorting 알고리즘을 구현하여 개별 SM의 커패시터 전압이 균등하게 일정 값을 유지하도록 하였다. 제안하는 MMC의 성능평가를 위하여 PSCAD/EMTDC 프로그램을 이용하여 3상 11-level MMC를 모의하였다.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.3
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• pp.74-81
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• 2019

Herein, we performed a comparative study on approximate multi-objective design optimization, to realize a structural design to improve the weight and vibration performances of the knuckle - a car suspension component - considering various load conditions and vibration characteristics. In the approximate multi-objective optimization process, a regression meta-model was generated using the response surfaces method (RSM), while Kriging and back-propagation neural network (BPN) methods were applied for interpolation meta-modeling. The Pareto solutions, multi-objective optimal solutions, were derived using the non-dominated sorting genetic algorithm (NSGA-II). In terms of the knuckle design considered in this study, the characteristics and influence of the meta-model on multi-objective optimization were reviewed through a comparison of the approximate optimization results with the meta-models and the actual optimization.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.5
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• pp.61-69
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• 2017

The study on interference channel is very important information theoretically and many studies have been done on it. However, even in the simplest case, even in the case of two user interfering channels, the channel capacity is not yet known except in special cases. Recently, research on the multiplexing gain that shows the tendency of the transmission rate in the high signal to noise ratio (SNR) band has been actively carried out, instead of accurately grasping the channel capacity. Obtaining optimal multiplexing gain can reveal trends in channel capacity at high signal-to-noise ratio bands. In an interfering channel with two users, the best multiplexing gain can be obtained by eliminating the interference. However, recent research shows that when the number of users is more than three, the optimal multiplexing gain can not be obtained only by zero forcing and a new technique called interference sorting is needed. There are two types of interference sorting techniques. Beamforming A method of effectively separating signals and interference by properly selecting matrices and constructing structured codes using rational numbers and irrational numbers. The interference alignment technique can achieve optimal multiplexing gain in various environments such as interference channel, X channel, compound broadcast channel, and multi hop network for multi source multi destination. In recent years, it has also been applied to distributed storage. Lee et al., "Lattice Code Interference Alignment in Cooperative Multipoint Transmission (COMP) for Interference Channels of Three Users", Journal of the Institute of Electronics Engineers, vol.49-TC,no.6,2012. In this paper, the DoF of delayed channel information is obtained.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.1-7
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• 2020

In modern society, as technology has advanced and human life area has expanded, there has been an increasing demand for high-quality voice and video communications services without restrictions on time and place. In response to this demand, satellite communications systems that provide a wide range of communications and that offer multiple access are evolving day by day. In satellite communications systems such as Digital Video Broadcasting - Return Channel Via Satellite (DVB-RCS) and Warfighter Information Network-Tactical (WIN-T), the multi-frequency time division multiple access (MF-TDMA) demand assigned multiple access (DAMA) scheme is used for efficient resource allocation. In this scheme, since the satellite terminals periodically request resources from the network controller, and the network controller dynamically allocates resources, it is necessary to arrange resource allocation information from time to time. Shortening of the alignment time is a more important factor in a satellite communications system in which a long transmission delay occurs due to long-distance transmission and reception. In this paper, we propose a sorting algorithm variable-selection scheme that shortens the sorting time by cross-selecting the sorting algorithm based on a threshold value, while setting the number of frames in the MF-TDMA DAMA satellite communications system as the threshold value.