• International Journal of Naval Architecture and Ocean Engineering
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• 제7권4호
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• pp.750-769
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• 2015

The geometry of engineering systems affects their performances. For this reason, the shape of engineering systems needs to be optimized in the initial design stage. However, engineering system design problems consist of multi-objective optimization and the performance analysis using commercial code or numerical analysis is generally time-consuming. To solve these problems, many engineers perform the optimization using the approximation model (response surface). The Response Surface Method (RSM) is generally used to predict the system performance in engineering research field, but RSM presents some prediction errors for highly nonlinear systems. The major objective of this research is to establish an optimal design method for multi-objective problems and confirm its applicability. The proposed process is composed of three parts: definition of geometry, generation of response surface, and optimization process. To reduce the time for performance analysis and minimize the prediction errors, the approximation model is generated using the Backpropagation Artificial Neural Network (BPANN) which is considered as Neuro-Response Surface Method (NRSM). The optimization is done for the generated response surface by non-dominated sorting genetic algorithm-II (NSGA-II). Through case studies of marine system and ship structure (substructure of floating offshore wind turbine considering hydrodynamics performances and bulk carrier bottom stiffened panels considering structure performance), we have confirmed the applicability of the proposed method for multi-objective side constraint optimization problems.

• 한국기계가공학회지
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• 제14권4호
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• pp.28-33
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• 2015

In this study, the optimal design for the support and the binding device for the protection of crops for the maximum allowable stress of the shape necessary to minimize volume has been proposed. Optimization of the support and the binding device for the crops should be designed to support businesses in terms of profit, in part to reduce the material, and to profit from the ease and speed of working that part of the farmers. We used CATIA for the mechanical design and the ANSYS program for the structural analysis. Additionally, the optimization was performed by PIAnO with seven design variables for the binding device and three parameters for the support. The weight method using a multi-objective function was also determined by the Pareto optimal solution. The volume of the binding device in the optimum design result was found to be reduced by 16%, from $2.278e-005m^3to1.912e-005m^3$. From the result, we confirmed the effectiveness of the design method proposed as a multi-objective function optimization problem.

• 대한기계학회논문집A
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• 제39권5호
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• pp.535-541
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• 2015

본 연구에서는 벽걸이 모니터 브라켓 암의 다중목적 근사최적설계를 수행하였다. 이를 위해 브라켓 암의 자유도를 고려하여 평면내의 회전 각도를 선정해 응력과 처짐량이 크게 발생하는 경우에 대한 최적화 문제를 정식화 하였다. 직교배열표와 반응표면법을 사용하여 평균 및 파라미터 분석을 통해 성능지수에 대한 설계변수 민감도를 확인하였으며, 중심합성계획법과 D-최적 계획법을 사용하여 목적함수와 제한조건함수에 대하여 반응표면 근사모델을 생성하고 $R^2$ 값을 통해 정확도를 평가하였다. 이를 비지배 분류 유전알고리즘에 적용하여 최적화를 수행하고 유한요소해석을 통해 검증하였다. 또한, 중심합성 계획법과 D-최적 계획법을 이용한 최적해를 비교 분석하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권12호
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• pp.5328-5346
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• 2016

An optimal power control algorithm based on convex optimization is proposed for base stations in long term evolution networks. An objective function was formulated to maximize the proportional fairness of the networks. The optimal value of the objective function was obtained using convex optimization and distributed methods based on the path loss model between the base station and users. Field tests on live networks were conducted to evaluate the performance of the proposed algorithm. The experimental results verified that, in a multi-cell multi-user scenario, the proposed algorithm increases system throughputs, proportional fairness, and energy efficiency by 9, 1.31 and 20.2 %, respectively, compared to the conventional fixed power allocation method.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1998년도 봄 학술발표회 논문집
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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.

• International Journal of Reliability and Applications
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• 제12권2호
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• pp.79-94
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• 2011

Redundancy-reliability allocation problems in multi-stage series-parallel systems are addressed in this study. Fuzzy programming techniques are proposed for finding satisfactory solutions. First, a multi-objective programming model is formulated for simultaneously maximizing system reliability and minimizing system total cost. Due to the nature of uncertainty in the problem, the fuzzy set theory and technique are used to convert the deterministic multi-objective programming model into a fuzzy nonlinear programming problem. A heuristic method is developed to get satisfactory solutions for the fuzzy nonlinear programming problem. A Pareto optimal solution is found with maximal degree of satisfaction from the interception area of fuzzy sets. A case study that is related to the electronic control unit installed on aircraft engine over-speed protection system is used to implement the developed approach. Results suggest that the developed fuzzy multi-objective programming model can effectively resolve the fuzzy and uncertain problem when design goals and constraints are not clearly confirmed at the initial conceptual design phase.

• Journal of Computational Design and Engineering
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• 제2권3호
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• pp.157-164
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• 2015

This paper discusses an optimization-based approach for the design of a product platform for industrial three-axis linear-type robots, which are widely used for handling objects in manufacturing lines. Since the operational specifications of these robots, such as operation speed, working distance and orientation, weight and shape of loads, etc., will vary for different applications, robotic system vendors must provide various types of robots efficiently and effectively to meet a range of market needs. A promising step toward this goal is the concept of a product platform, in which several key elements are commonly used across a series of products, which can then be customized for individual requirements. However the design of a product platform is more complicated than that of each product, due to the need to optimize the design across many products. This paper proposes an optimization-based fundamental framework toward the design of a product platform for industrial three-axis linear-type robots; this framework allows the solution of a complicated design problem and builds an optimal design method of fundamental features of robot frames that are commonly used for a wide range of robots. In this formulation, some key performance metrics of the robot are estimated by a reducedorder model which is configured with beam theory. A multi-objective optimization problem is formulated to represent the trade-offs among key design parameters using a weighted-sum form for a single product. This formulation is integrated into a mini-max type optimization problem across a series of robots as an optimal design formulation for the product platform. Some case studies of optimal platform design for industrial three-axis linear-type robots are presented to demonstrate the applications of a genetic algorithm to such mathematical models.

• 전기학회논문지
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• 제62권1호
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• pp.49-56
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• 2013

In this paper, for constrained optimization problem, one multi-objective optimization algorithm that ensures both performance robustness and constraint feasibility is proposed when uncertainties are involved in design variables. In the proposed algorithm, the gradient index of objective function assisted by design sensitivity with the help of finite element method is applied to evaluate robustness; the reliability calculated by the sensitivity-assisted Monte Carlo simulation method is used to assess the feasibility of constraint function. As a demonstration, the performance and numerical efficiency of the proposed method is investigated through application to the optimal design of TEAM problem 22--a superconducting magnetic energy storage system.

• 한국지진공학회논문집
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• 제11권6호
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• pp.1-14
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• 2007

인접 구조물의 지진응답 제어를 위한 비선형 감쇠시스템의 최적 설계 방법에 관하여 연구하였다. 최적 설계를 위한 목적 함수로는 구조물의 응답과 감쇠기의 총 사용량을 고려하였으며, 상충하는 두 목적함수를 합리적인 수준에서 동시에 최소화하는 해를 구하기 위하여 유전자 알고리즘에 기반한 다목적 최적화 방법을 도입하였다. 또한, 최적화 과정에서 요구되는 비선형 시간이력해석을 수행하지 않고도, 비선형 이력감쇠기로 연결된 구조물의 지진응답을 효율적으로 평가하기 위하여 추계학적 선형화 방법을 접목하였다. 제시하는 방법의 효율성을 검증하기 위한 수치 예로서 20층과 10층의 인접 빌딩을 고려하였으며, 두 빌딩을 연결하는 비선형 감쇠시스템으로는 입력전압의 크기에 따라 변화하는 감쇠성능을 보이는 MR 감쇠기를 도입하였다. 제시하는 방법을 통하여 MR 감쇠기의 각 층별 최적 개수 및 감쇠용량을 결정할 수 있었으며, 이는 일반적인 균등분포 시스템에 비해 유사한 제어성능을 보이면서도 훨씬 경제적이었다. 또한, 인접구조물간 충돌에 대하여도 확률적으로 안정적인 거동을 보임을 검증하였으며, 제시하는 방법이 준능동 제어시스템의 최적 배치를 결정하기 위한 설계문제에도 적용할 수 있음을 보였다.

• Structural Engineering and Mechanics
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• 제68권5호
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• pp.633-638
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• 2018

One of the important problems in the vehicle design is vehicle handling and stability. Effective parameters which should be considered in the vehicle handling and stability are roll angle, camber angle and scrub radius. In this paper, a planar vehicle model is considered that two right and left suspensions are double wishbone suspension system. For a better analysis of the suspension geometry, a kinestatic model of vehicle is considered which instantaneous kinematic and statics relations are analyzed simultaneously. In this model, suspension geometry is considered completely. In order to optimum design of double wishbones suspension system, a multi-objective genetic algorithm is applied. Three important parameters of suspension including roll angle, camber angle and scrub radius are taken into account as objective functions. Coordinates of suspension hard points are design variables of optimization which optimum values of them, corresponding to each optimum point, are obtained in the optimization process. Pareto solutions for three objective functions are derived. There are important optimum points in these Pareto solutions which each point represents an optimum status in the model. In other words, corresponding to any optimal point, a specific geometric position is determined for the suspension hard points. Each of the obtained points in the Pareto optimization can be selected for a special design purpose by designer to create an optimum condition in the vehicle handling and stability.