• Journal of Korean Association for Spatial Structures
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• v.13 no.3
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• pp.91-98
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• 2013

A multi-input single-output (MISO) semi-active control systems were studied by many researchers. For more improved vibration control performance, a structure requires more than one control device. In this paper, multi-input multi-output (MIMO) semi-active fuzzy controller has been proposed for vibration control of seismically excited small-scale buildings. The MIMO fuzzy controller was optimized by multi-objective genetic algorithm. For numerical simulation, five-story example building structure is used and two MR dampers are employed. For comparison purpose, a clipped-optimal control strategy based on acceleration feedback is employed for controlling MR dampers to reduce structural responses due to seismic loads. Numerical simulation results show that the MIMO fuzzy control algorithm can provide superior control performance to the clipped-optimal control algorithm.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.87.1-87.1
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• 2005

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.93.3-93
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• 2002

$\textbullet$ Co-evolutionary algorithms $\textbullet$ Nash Genetic Algorithms $\textbullet$ Multi-objective Optimization $\textbullet$ Distance dependent mutation $\textbullet$ Pareto Optimality

• Journal of Electrical Engineering and Technology
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• v.11 no.5
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• pp.1404-1411
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• 2016

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.1
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• pp.179-193
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• 1995

A multi-objective, single-stage scheduling problem with stochastic processing times is considered where the objective is to simultaneously minimize the expected value and the variance of total flowtime, and the mean probability of tardiness. In cases where processing times follow normal distributions, a method using pairwise interchange of two jobs(PITJ) is proposed to generate a set of the approximate efficient schedules. The efficient schedules are not dominated by the criterion vectors of any other permutation schdules in the feasible region. Numerical experiments performed to ascertain the effectiveness of PITJ algorithm are also reported in the results.

• Management Science and Financial Engineering
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• v.3 no.1
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• pp.75-88
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• 1997

Tabu search (TS) has been successfully applied for solving many complex combinatorial optimization problems in the areas of operations research and production control. However, TS is for single-objective problems in its present form. In this article, a TS-based heuristic is developed to determine Pareto-efficient solutions to a multi-objective combinatorial optimization problem. The developed algorithm is then applied to the discrete optimal design problem in statistics to demonstrate its usefulness.

• Journal of the Korean Operations Research and Management Science Society
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• v.16 no.2
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• pp.1-12
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• 1991

The purpose of this paper are to find the relations between efficient faces and the regions of weights on the objective functions in Multi-objective Linear Programming. First, we define the region of weights corresponding to an efficient face, and find the changing pattern within the region of weights. Second, we find the eqution of the dimensional relation between the efficient face and the region of weight corrsponding to it.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.207-210
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• 2009

According to the recent demand for materials for use in various displays and solid state lightings, new phosphors with improved performance have been pursued consistently. Multi objective genetic algorithm assisted combinatorial material search (MOGACMS) strategies have been applied to various multi-compositional inorganic systems to search for new phosphors and to optimize the properties of phosphors.

• Journal of Korean Society of Steel Construction
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• v.12 no.5 s.48
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• pp.503-513
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• 2000

This study treats the criteria, considering the fuzziness occurred by optimization design. And we applied two weighting methods to show the relative importance of criteria. This study develops multi-objective optimization programs implementing plain stress analysis by FEM and discrete optimization design uniformaly. The developed program performs a sample design of 10-member steel truss. This study can carry over the multi-objective optimization based on total system fuzzy-genetic algorithms while performing the stress analysis and optimization design. Especially, when general optimization with unreliable constraints is cannot be solve this study can make optimization design closed to realistic with fuzzy theory.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.611-616
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• 2008

Error correcting codes (ECCs) are commonly used to protect against the soft errors. Single error correcting and double error detecting (SEC-DED) codes are generally used for this purpose. The proposed approach in this paper selectively reduced power consumption, delay, and area in single-error correcting, double error-detecting checker circuits that perform memory error correction. The multi-objective genetic algorithm is employed to solve the non -linear optimization problem. The proposed method allows that user can choose one of different non-dominated solutions depending on which consideration is important among them. Because we use multi-objective genetic algorithm, we can find various dominated solutions. Therefore, we can choose the ECC according to the important factor of the power, delay and area. The method is applied to odd-column weight Hsiao code which is well- known ECC code and experiments were performed to show the performance of the proposed method.