• Journal of the Earthquake Engineering Society of Korea
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• v.6 no.5
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• pp.37-43
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• 2002

In this paper, an integrated optimum design method for hybrid structural control system is studied. Not only the distribution and the capacity of passive devices but also those of active devices, and the controllers are treated as design variables in the proposed approach. Multi-objective optimization problem is formulated by using the preference function, which is newly defined in this study. Genetic algorithm is adopted as a numerical searching technique in order to simultaneously find the optimum solutions. The validity of the proposed method is verified through the example designs and the numerical simulations of an earthquake excited multi-degrees-of-freedom structure.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.145-152
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• 2021

In the Recent times, various technological enhancements in the field of artificial intelligence and big data has been noticed. This advancement coupled with the evolution of the 5G communication and Internet of Things technologies, has helped in the development in the domain of smart mine construction. The development of unmanned vehicles with enhanced and smart scheduling system for open-pit mine transportation is one such much needed application. Traditional open-pit mining systems, which often cause vehicle delays and congestion, are controlled by human authority. The number of sensors has been used to operate unmanned cars in an open-pit mine. The sensors haves been used to prove the real-time data in large quantity. Using this data, we analyses and create an improved transportation scheduling mechanism so as to optimize the paths for the vehicles. Considering the huge amount the data received and aggregated through various sensors or sources like, the GPS data of the unmanned vehicle, the equipment information, an intelligent, and multi-target, open-pit mine unmanned vehicle schedules model was developed. It is also matched with real open-pit mine product to reduce transport costs, overall unmanned vehicle wait times and fluctuation in ore quality. To resolve the issue of scheduling the transportation, we prefer to use algorithms based on artificial intelligence. To improve the convergence, distribution, and diversity of the classic, rapidly non-dominated genetic trial algorithm, to solve limited high-dimensional multi-objective problems, we propose a decomposition-based restricted genetic algorithm for dominance (DBCDP-NSGA-II).

• Smart Structures and Systems
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• v.26 no.5
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• pp.545-558
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• 2020

A design method of a Multiple Tuned Mass Damper (MTMD) system is presented for wind induced vibration control of a cable-supported roof structure. Modal contribution analysis is carried out to determine the dominating modes of the structure for the MTMD design. Two MTMD systems are developed for two most dominating modes. Each MTMD system is composed of multiple TMDs with small masses spread at multiple locations with large responses in the corresponding mode. Frequencies of TMDs are distributed uniformly within a range around the dominating frequencies of the roof structure to enhance the robustness of the MTMD system against uncertainties of structural frequencies. Parameter optimizations are carried out by minimizing objective functions regarding the structural responses, TMD strokes, robustness and mass cost. Two optimization approaches are used: Single Objective Approach (SOA) using Sequential Quadratic Programming (SQP) with multi-start method and Multi-Objective Approach (MOA) using Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The computation efficiency of the MOA is found to be superior to the SOA with consistent optimization results. A Pareto optimal front is obtained regarding the control performance and the total weight of the TMDs, from which several specific design options are proposed. The final design may be selected based on the Pareto optimal front and other engineering factors.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.7
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• pp.839-846
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• 1999

This paper presents an efficient algorithm for determining the location, size and number of capacitors in unbalanced radial distribution system. The objective function formulated consists of two terms: cost for energy loss and cost related to capacitor purchase and capacitor installation. The cost function associated with capacitor placement is considered as step function due to banks of standard discrete capacities. Genetic algorithms(GA) are used to obtain the population is derived. The strings in each population consist of the bus number index and size of capacitors to be installed. In order to determine the number of capacitor placement, the length mutation operator is used. Its efficiency is proved through the application in unbalanced radial distribution systems made of 10 buses with 9 distribution lines and 25 buses with 24 distribution lines.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.4
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• pp.187-192
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• 2014

Lot-streaming is the process of splitting a job (lot) into sublots to allow the overlapping of operations between successive machines in a multi-stage production system. A new genetic algorithm (NGA) is proposed for an n-job, m-machine, lot-streaming flow shop scheduling problem with equal-size sublots in which the objective is to minimize the total stretch. The stretch of a job is the ratio of the amount of time the job spent before its completion to its processing time. NGA replaces the selection and mating operators of genetic algorithms (GAs) by marriage and pregnancy operators and incorporates the idea of inter-chromosomal dominance and individuals' similarities. Extensive computational experiments for medium to large-scale lot-streaming flow-shop scheduling problems have been conducted to compare the performance of NGA with that of GA.

• Proceedings of the Korea Concrete Institute Conference
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• 2003.05a
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• pp.853-858
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• 2003

A new method is proposed to obtain bond-slip model for an adhesive joint between FRP and concrete. Interface element, which can describe the bond behavior, is developed in order to overcome the restriction that complex constitutive relations cannot be modeled in analytic solution. Calibrating numerical bond-slip model to experimental results, multi-objective optimization problem is constructed by physical programming method, and is solved using genetic algorithm. The validity of proposed method is demonstrated by comparing known analytic solution and numerically optimized solution.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.343-346
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• 2008

휴머노이드 로봇이 넘어질 경우, 충격에 의한 손상이 발생할수 있다. 이를 최소화하는 넘어짐 자세의 생성을 위하여 개선된 PGA 기반의 탐색기법을 제안한다. 다목적함수를 고려한 군집 간 이주방식의 효율적 조합을 통해 넘어짐 충격을 최소화하는 각 관절 궤적을 구할수 있도록 하였다. 제안된 기법의 검증을 위하여 Sony QRIO 로봇에 대해서 ODE 기반의 Webots 시뮬레이션을 이용하여 실험을 수행하였다.

• Journal of Aerospace System Engineering
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• v.15 no.2
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• pp.1-9
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• 2021

In this paper, a thickness compensation function is introduced to consider the shear deformation and warping effect resulting from increased thickness in the composite multi-cell wing box. The thickness compensation function is used to perform the structure optimization of the multi-cell. It is determined by minimizing the error of an analytical formula using solid mechanics and the Ritz method. It is used to define a structural performance prediction expression due to the increase in thickness. The parameter is defined by the number of spars and analyzed by the critical buckling load and the limited failure index as a response. Constraints in structural optimization are composed of displacements, torsional angles, the critical buckling load, and the failure index. The objective function is the mass, and its optimization is performed using a genetic algorithm.

• Journal of the Earthquake Engineering Society of Korea
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• v.14 no.2
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• pp.1-13
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• 2010

This paper proposes an optimal design method for the nonlinear seismic isolated bridge. The probabilities of failure at the pier and the seismic isolator are considered as objective functions for optimal design, and a multi-objective optimization technique is employed to efficiently explore a set of multiple solutions optimizing mutually-conflicting objective functions at the same time. In addition, a stochastic linearization method is incorporated into the multi-objective optimization framework in order to effectively estimate the stochastic responses of the bridge without performing numerous nonlinear time history analyses during the optimization process. As a numerical example to demonstrate the efficiency of the proposed method, the Nam-Han river bridge is taken into account, and the proposed method and the existing life-cycle-cost based design method are both applied for the purpose of comparing their seismic performances. The comparative results demonstrate that the proposed method not only shows better seismic performance but also is more economical than the existing cost-based design method. The proposed method is also proven to guarantee improved performance under variations in seismic intensity, in bandwidth and in the predominant frequency of the seismic event.

• Proceedings of the KIEE Conference
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• 1999.07a
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• pp.214-216
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• 1999

This paper discussed an optimal designs of 2 pole fan motors in refrigerator using a Niching Algorithm. We applied a Niching method to multi-objective optimal design of air gap construct. This Niching genetic algorithm is called "Restricted Competition Selection"(RCS) that is suitable for real world problem such as shape or structural optimization of electromagnetic device. The finite element method being used for nonlinear numerical characteristic analysis is provided exact solution in the system. Through this process is reduced the cogging torque ripple in air gap.