• Title/Summary/Keyword: multi-objective design strategy

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System Decomposition Technique using Multiple Objective Genetic Algorithm (다목적 유전알고리듬을 이용한 시스템 분해 기법)

  • Park, Hyung-Wook;Kim, Min-Soo;Choi, Dong-Hoon
    • Proceedings of the KSME Conference
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    • 2001.06c
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    • pp.170-175
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    • 2001
  • The design cycle associated with large engineering systems requires an initial decomposition of the complex system into design processes which are coupled through the transference of output data. Some of these design processes may be grouped into iterative subcycles. In analyzing or optimizing such a coupled system, it is essential to determine the best order of the processes within these subcycles to reduce design cycle time and cost. This is accomplished by decomposing large multidisciplinary problems into several multidisciplinary analysis subsystems (MDASS) and processing it in parallel. This paper proposes new strategy for parallel decomposition of multidisciplinary problems to improve design efficiency by using the multiple objective genetic algorithm (MOGA), and a sample test case is presented to show the effects of optimizing the sequence with MOGA.

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Multiobjective optimization strategy based on kriging metamodel and its application to design of axial piston pumps (크리깅 메타모델에 기반한 다목적최적설계 전략과 액셜 피스톤 펌프 설계에의 응용)

  • Jeong, Jong Hyun;Baek, Seok Heum;Suh, Yong Kweon
    • Journal of Advanced Marine Engineering and Technology
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    • v.37 no.8
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    • pp.893-904
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    • 2013
  • In this paper, a Kriging metamodel-based multi-objective optimization strategy in conjunction with an NSGA-II(non-dominated sorted genetic algorithm-II) has been employed to optimize the valve-plate shape of the axial piston pump utilizing 3D CFD simulations. The optimization process for minimum pressure ripple and maximum pump efficiency is composed of two steps; (1) CFD simulation of the piston pump operation with various combination of six parameters selected based on the optimization principle, and (2) applying a multi-objective optimization approach based on the NSGA-II using the CFD data set to evaluate the Pareto front. Our exploration shows that we can choose an optimal trade-off solution combination to reach a target efficiency of the axial piston pump with minimum pressure ripple.

Multi-objective shape optimization of tall buildings considering profitability and multidirectional wind-induced accelerations using CFD, surrogates, and the reduced basis approach

  • Montoya, Miguel Cid;Nieto, Felix;Hernandez, Santiago
    • Wind and Structures
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    • v.32 no.4
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    • pp.355-369
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    • 2021
  • Shape optimization of tall buildings is an efficient approach to mitigate wind-induced effects. Several studies have demonstrated the potential of shape modifications to improve the building's aerodynamic properties. On the other hand, it is well-known that the cross-section geometry has a direct impact in the floor area availability and subsequently in the building's profitability. Hence, it is of interest for the designers to find the balance between these two design criteria that may require contradictory design strategies. This study proposes a surrogate-based multi-objective optimization framework to tackle this design problem. Closed-form equations provided by the Eurocode are used to obtain the wind-induced responses for several wind directions, seeking to develop an industry-oriented approach. CFD-based surrogates emulate the aerodynamic response of the building cross-section, using as input parameters the cross-section geometry and the wind angle of attack. The definition of the building's modified plan shapes is done adopting the reduced basis approach, advancing the current strategies currently adopted in aerodynamic optimization of civil engineering structures. The multi-objective optimization problem is solved with both the classical weighted Sum Method and the Weighted Min-Max approach, which enables obtaining the complete Pareto front in both convex and non-convex regions. Two application examples are presented in this study to demonstrate the feasibility of the proposed strategy, which permits the identification of Pareto optima from which the designer can choose the most adequate design balancing profitability and occupant comfort.

Multi-Point Aerodynamic Shape Optimization of Rotor Blades Using Unstructured Meshes

  • Lee, Sang-Wook;Kwon, Oh-Joon
    • International Journal of Aeronautical and Space Sciences
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    • v.8 no.1
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    • pp.66-78
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    • 2007
  • A multi-point aerodynamic shape optimization technique has been developed for helicopter rotor blades in hover based on a continuous adjoint method on unstructured meshes. The Euler flow solver and the continuous adjoint sensitivity analysis were formulated on the rotating frame of reference. The 'objective function and the sensitivity were obtained as a weighted sum of the values at each design point. The blade section contour was modified by using the Hicks-Henne shape functions. The mesh movement due to the blade geometry change was achieved by using a spring analogy. In order to handle the repeated evaluation of the design cycle efficiently, the flow and adjoint solvers were parallelized based on a domain decomposition strategy. A solution-adaptive mesh refinement technique was adopted for the accurate capturing of the wake. Applications were made to the aerodynamic shape optimization of the Caradonna-Tung rotor blades and the UH-60 rotor blades in hover.

Design of a decoupled PID controller via MOCS for seismic control of smart structures

  • Etedali, Sadegh;Tavakoli, Saeed;Sohrabi, Mohammad Reza
    • Earthquakes and Structures
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    • v.10 no.5
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    • pp.1067-1087
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    • 2016
  • In this paper, a decoupled proportional-integral-derivative (PID) control approach for seismic control of smart structures is presented. First, the state space equation of a structure is transformed into modal coordinates and parameters of the modal PID control are separately designed in a reduced modal space. Then, the feedback gain matrix of the controller is obtained based on the contribution of modal responses to the structural responses. The performance of the controller is investigated to adjust control force of piezoelectric friction dampers (PFDs) in a benchmark base isolated building. In order to tune the modal feedback gain of the controller, a suitable trade-off among the conflicting objectives, i.e., the reduction of maximum modal base displacement and the maximum modal floor acceleration of the smart base isolated structure, as well as the maximum modal control force, is created using a multi-objective cuckoo search (MOCS) algorithm. In terms of reduction of maximum base displacement and story acceleration, numerical simulations show that the proposed method performs better than other reported controllers in the literature. Moreover, simulation results show that the PFDs are able to efficiently dissipate the input excitation energy and reduce the damage energy of the structure. Overall, the proposed control strategy provides a simple strategy to tune the control forces and reduces the number of sensors of the control system to the number of controlled stories.

Multi-Stage Supply Chain Network Design Using a Cooperative Coevolutionary Algorithm Based on a Permutation Representation (순열 표현 기반의 협력적 공진화 알고리즘을 사용한 다단계 공급사슬 네트워크의 설계)

  • Han, Yong-Ho
    • 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.

Multi-Objective Optimization of a Fan Blade Using NSGA-II (NSGA-II 를 통한 송풍기 블레이드의 다중목적함수 최적화)

  • Lee, Ki-Sang;Kim, Kwang-Yong;Samad, Abdus
    • Proceedings of the KSME Conference
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    • 2007.05b
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    • pp.2690-2695
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    • 2007
  • This work presents numerical optimization for design of a blade stacking line of a low speed axial flow fan with a fast and elitist Non-Dominated Sorting of Genetic Algorithm (NSGA-II) of multi-objective optimization using three-dimensional Navier-Stokes analysis. Reynolds-averaged Navier-Stokes (RANS) equations with ${\kappa}-{\varepsilon}$ turbulence model are discretized with finite volume approximations and solved on unstructured grids. Regression analysis is performed to get second order polynomial response which is used to generate Pareto optimal front with help of NSGA-II and local search strategy with weighted sum approach to refine the result obtained by NSGA-II to get better Pareto optimal front. Four geometric variables related to spanwise distributions of sweep and lean of blade stacking line are chosen as design variables to find higher performed fan blade. The performance is measured in terms of the objectives; total efficiency, total pressure and torque. Hence the motive of the optimization is to enhance total efficiency and total pressure and to reduce torque.

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Multi-Objective Shape Optimization of an Axial Fan Blade

  • Samad, Abdus;Lee, Ki-Sang;Kim, Kwang-Yong
    • International Journal of Air-Conditioning and Refrigeration
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    • v.16 no.1
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    • pp.1-8
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    • 2008
  • Numerical optimization for design of a blade stacking line of a low speed axial flow fan with a fast and elitist Non-Dominated Sorting of Genetic Algorithm(NSGA-II) of multi-objective optimization using three-dimensional Navier-Stokes analysis is presented in this work. Reynolds-averaged Navier-Stokes(RANS) equations with ${\kappa}-{\varepsilon}$ turbulence model are discretized with finite volume approximations and solved on unstructured grids. Regression analysis is performed to get second order polynomial response which is used to generate Pareto optimal front with help of NSGA-II and local search strategy with weighted sum approach to refine the result obtained by NSGA-II to get better Pareto optimal front. Four geometric variables related to spanwise distributions of sweep and lean of blade stacking line are chosen as design variables to find higher performed fan blade. The performance is measured in terms of the objectives; total efficiency, total pressure and torque. Hence the motive of the optimization is to enhance total efficiency and total pressure and to reduce torque.

A Study on the Characteristics of Branded Environments in Hotel Spaces (호텔 공간의 브랜드화 환경 특성 연구)

  • Lee, Hwa-Kyoung;Ahn, Seongmo
    • Korean Institute of Interior Design Journal
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    • v.23 no.1
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    • pp.143-151
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    • 2014
  • Nowadays, space branding becomes more important since it reflects and synthesizes the diverse experiences of the consumer. The objective of the research is to present the new possibilities that space branding offers by analyzing the brand strategy and the design characteristics of branded hotels, which are being projected as constructed branded environments. By integrating the brand with visible or invisible elements of the hotel, such as unique space planning, service, and consumer experience, a branded hotel can be a good vehicle to reflect fast changing consumer lifestyles and trends; it enables the consumer to experience brands in his or her everyday life, and it conveys the overall image of the brand by considering the consumer's multi-sensual experiences. The study processed with theoretical research which is related to the hotel space and branded environment. Four brands were selected with distinct business area and brand strategy, and studied to analyze the strategy and the characteristics of the branded environment in a branded hotel. In particular, the case study attempted to evaluate the distinctiveness of the branded hotel's spatial design by comparing each brand's representative flagship store with the hotel. As a result, four characteristics of branded environments in branded hotels were identified, namely, strengthen brand image, consistent brand strategy, extend brand perception, spatialize brand experience. Armani emphasizes their consistent brand image by applying similar design methods in both retail stores and hotel spaces. IKEA, in contrast, applies not their design identity but their brand concepts like practicality, efficiency, and low prices. Pantone gives an expanded brand experience by using synesthetic sensual stimulation using their color system. Missoni mixes and composes their patterns and materials in a three-dimensional manner and strengthens design possibilities and spatiality. This study suggests specific design methods to construct a branded environment in a branded hotel and offers new strategic directions for space branding.

Application of Fuzzy Decision to Optimization of Induction Motor Design (퍼지 결정법을 적용한 유도전동기의 최적 설계)

  • 박정태;정현교
    • Journal of the Korean Magnetics Society
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    • v.7 no.2
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    • pp.103-108
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    • 1997
  • In this paper, the application of fuzzy decision to optimization of induction motor design is proposed. This method can reflect the designer's experience, view, and judgment, but also can be applied to multi-objective optimization design easily. The electromagnetic performance of the induction motor are calculated by means of the equivalent magnetic circuit method. The design method is The $D^2L$ method which is combined with fuzzy decision and optimization algorithm. As the optimization algorithm, the evolution strategy(ES) is applied. The proposed algorithm is applied to a multiobjective optimization of an induction motor design where the motor should have less weight and, at the same time, have higher efficiency and power factor at rated operating points.

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