• Earthquakes and Structures
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• v.10 no.6
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• pp.1451-1465
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• 2016

The effectiveness of base isolation (BI) systems for mitigation of seismic vibration of bridges have been extensively studied in the past. It is well established in those studies that the performance of BI system is largely dependent on the characteristics of isolator yield strength. For optimum design of such systems, normally a standard nonlinear optimization problem is formulated to minimize the maximum response of the structure, referred as Stochastic Structural Optimization (SSO). The SSO of BI system is usually performed with reference to a problem of unconstrained optimization without imposing any restriction on the maximum isolator displacement. In this regard it is important to note that the isolator displacement should not be arbitrarily large to fulfil the serviceability requirements and to avoid the possibility of pounding to the adjacent units. The present study is intended to incorporate the effect of excessive isolator displacement in optimizing BI system to control seismic vibration effect of bridges. In doing so, the necessary stochastic response of the isolated bridge needs to be optimized is obtained in the framework of statistical linearization of the related nonlinear random vibration problem. A simply supported bridge is taken up to elucidate the effect of constraint condition on optimum design and overall performance of the isolated bridge compared to that of obtained by the conventional unconstrained optimization approach.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.177-182
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• 2021

Generally, the linear programming (LP) with O(n⁴) time complexity is applied to mixture optimization problem that can be produce the given ingredients grade product with minimum cost from mixture of various raw materials. This paper suggests heuristic algorithm with O(n log n) time complexity to obtain the solution of this problem. The proposed algorithm meets the content range of the components required by the alloy steel plate while obtaining the minimum raw material cost, decides the quantity of raw material that is satisfied with ingredients grade for ascending order of unit cost. Although the proposed algorithm applies simple decision technique with O(n log n) time complexity, it can be obtains same solution as or more than optimization technique of linear programing.

• Steel and Composite Structures
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• v.42 no.4
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• pp.489-499
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• 2022

This paper proposes a numerical optimization method to design the mesoscale architecture of textile composite for simultaneously enhancing mechanical and thermal properties, which compete with each other making it difficult to design intuitively. The base cell of the periodic warp and fill yarn system is served as the design space, and optimal fibre yarn geometries are found by solving the optimization problem through the proposed method. With the help of homogenization method, analytical formulae for the effective material properties as functions of the geometry parameters of plain-woven textile composites were derived, and they are used to form the inverse homogenization method to establish the design problem. These modules are then put together to form a multiobjective optimization problem, which is formulated in such a way that the optimal design depends on the weight factors predetermined by the user based on the stiffness and thermal terms in the objective function. Numerical examples illustrate that the developed method can achieve reasonable designs in terms of fibre yarn paths and geometries.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1097-1108
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• 2022

This paper aimed to design and implement an EMS for real-time power generation control based on wake effect optimization of wind farm, and then to test it in commercial operating wind farm. For real-time control, we proposed the wake band-based optimization and setting the wake effect distance limit, and when the wake effect distance limit was set to 7D in the actual wind farm layout, the calculation time was improved by about 93.94%. In addition, we designed and implemented the script-based EMS for flexible operation logic management in preparation for unexpected issues during testing, and it was installed and tested on a wind farm in commercial operation. However, three issues arose during the testing process. These are the communication interface problem of meteorological tower, the problem of an abnormal wake effect, and the problem of wind turbine yaw control. These issues were solved by modifying the operation logic using EMS's script editor, and the test was successfully completed in the wind farm in commercial operation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2490-2506
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• 2022

In Mobile Edge Computing (MEC), attackers can speculate and mine sensitive user information by eavesdropping wireless channel status and offloading usage pattern, leading to user privacy leakage. To solve this problem, this paper proposes a Privacy-preserving and Energy-efficient Offloading Algorithm (PEOA) based on Lyapunov optimization. In this method, a continuous Markov process offloading model with a buffer queue strategy is built first. Then the amount of privacy of offloading usage pattern in wireless channel is defined. Finally, by introducing the Lyapunov optimization, the problem of minimum average energy consumption in continuous state transition process with privacy constraints in the infinite time domain is transformed into the minimum value problem of each timeslot, which reduces the complexity of algorithms and helps obtain the optimal solution while maintaining low energy consumption. The experimental results show that, compared with other methods, PEOA can maintain the amount of privacy accumulation in the system near zero, while sustaining low average energy consumption costs. This makes it difficult for attackers to infer sensitive user information through offloading usage patterns, thus effectively protecting user privacy and safety.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.187-198
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• 2022

This paper addresses the maintenance optimization problem in multi-component systems in which parts are connected in series, carrying out several missions interspersed with scheduled finite breaks. Due to limited time or resources, maintenance actions can be only carried out on a limited set of components. The decision maker then has to decide which components to maintain to ensure a pre-specified performance level during next mission. Most of the existing models in the literature usually assume only one system and enough spare parts. However, there are situations in which maintenance is required for multiple systems of the same type. To overcome this restrictive assumption, this study optimizes the maintenance problem considering the lack of repair parts and cannibalism for many identical systems. This study presents two optimization models with different objectives to solve the problem and analyzes the results so that the decision maker can decide. The results of this study are expected to be used for the maintenance of multiple systems of the same type, such as swarm drones.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.4
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• pp.37-45
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• 2022

In this paper, a multi agent-multi task assignment problem, which is a representative problem of combinatorial optimization, is presented. The objective of the problem is to determine the coordinated agent-task assignment that maximizes the sum of the achievement rates of each task. The achievement rate is represented as a concave down increasing function according to the number of agents assigned to the task. The problem is expressed as an NP-hard problem with a non-linear objective function. In this paper, to solve the assignment problem, we propose a hybrid cross-entropy algorithm as an effective and efficient solution methodology. In fact, the general cross-entropy algorithm might have drawbacks (e.g., slow update of parameters and premature convergence) according to problem situations. Compared to the general cross-entropy algorithm, the proposed method is designed to be less likely to have the two drawbacks. We show that the performances of the proposed methods are better than those of the general cross-entropy algorithm through numerical experiments.

• Computational Structural Engineering : An International Journal
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• v.1 no.2
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• pp.89-96
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• 2001

A study on the topology optimization of a Hard-Disk-Driver(HDD) actuator arm is presented. The purpose of the present wert is to increase the natural frequency of tole first lateral mode of the HDD actuator arm under the constraint of total moment of inertia, so as to facilitate the position control of the high speed actuator arm. The first lateral mode is an important factor in the position control process. Thus the topology optimization for 2-D model of the HDD actuator arm is considered. A new objective function corresponding to multieigenvalue optimization is suggested to improve the solution of the eigenvalue optimization problem. The material density of the structure is treated as the design variable and the intermediate density is penalized. The effects of different element types and material property functions on the final topology are studied. When the problem is discretized using 8-node element of a uniform density, tole smoothly-varying density field is obtained without checker-board patterns incurred. AS a result of 7he study, an improved design of the HDD actuator arm is suggested. Dynamic characteristics of the suggested design are compared computationally with those of the old design. With the same amount of the moment of inertia, the natural frequency of the first lateral mode of the suggested design is subsequently increased over the existing one.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.10
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• pp.1558-1565
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• 2004

It is important to determine supporting locations for structural stability when a structure is loaded with non-uniform load or supporting locations as well as the number of the supporting structures are restricted by the problem of space. Moreover, the supporting location optimization of complex structure in real world is frequently faced with discontinuous design space. Therefore, the traditional optimization methods based on derivative are not suitable Whereas, Genetic Algorithm (CA) based on stochastic search technique is a very robust and general method. The KSTAR in-vessel control coil installed in vacuum vessel is loaded with non- uniform electro-magnetic load and supporting locations are restricted by the problem of space. This paper shows the supporting location optimization for structural stability of the in-vessel control coil. Optimization has been performed by means of a developed program. It consists of a Finite Element Analysis interfaced with a Genetic Algorithm. In addition, this paper presents an algorithm to find an optimum solution in discontinuous space using continuous design variables.

• Journal of Electrical Engineering and Technology
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• v.6 no.2
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• pp.174-181
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• 2011

This paper proposes a novel binary ant colony optimization (NBACO) method. The proposed NBACO is based on the concept and principles of ant colony optimization (ACO), and developed to solve the binary and combinatorial optimization problems. The concept of conventional ACO is similar to Heuristic Dynamic Programming. Thereby ACO has the merit that it can consider all possible solution sets, but also has the demerit that it may need a big memory space and a long execution time to solve a large problem. To reduce this demerit, the NBACO adopts the state probability matrix and the pheromone intensity matrix. And the NBACO presents new updating rule for local and global search. The proposed NBACO is applied to test power systems of up to 100-unit along with 24-hour load demands.