• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.5
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• pp.433-441
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• 2011

The optimization of a centrifugal compressor was conducted. The ANN (Artificial Neural Network) was adopted as an optimization algorithm, and it was learned and trained with the DOE (Design of Experiment). In the DOE, it was predicted the main effect and the interaction effect of design variables to the objective function. The ANN was improved in the optimization process using the GA (Genetic Algorithm). When any output at each generation was reached a standard level, it was re-calculated by the CFD (Computational Fluid Dynamics) and it was applied to develop a new ANN. After 6th generation, the prediction difference between ANN and CFD was less than 1%. A pareto of the efficiency versus the pressure ratio was obtained through the 21th generation. Using this method, the computational time for the optimization was equivalent to the time consumed by the gradient method, and the optimized results of multi-objective function were obtained.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.209-216
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• 2005

The controller that can control the smart base isolation system consisting of M damper and friction pendulum systems(FPS) is developed in this study. A fuzzy logic controller (FLC) is used to modulate the M damper force because the FLC has an inherent robustness and ability to handle non-linearities and uncertainties. A genetic algorithm (GA) is used for optimization of the FLC. When earthquake excitations are applied to the structures equipped with smart base isolation system, the relative displacement at the isolation level as well as the acceleration of the structure should be regulated under appropriate level. Thus, NSGA-II(Non-dominated Sorting Genetic Algorithm) is employed in this study as a multi-objective genetic algorithm to meet more than two control objectives, simultaneously. NSGA-II is used to determine appropriate fuzzy control rules as well to adjust parameters of the membership functions. Effectiveness of the proposed method for optimal design of the FLC is judged based on computed responses to several historical earthquakes. It has been shown that the proposed method can efficiently find Pareto optimal sets that can reduce both structural acceleration and base drift from numerical studies.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.9
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• pp.424-430
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• 2001

A multi-level optimal power flow(OPF) algorithm has been evolved from a simple two stage optimal Power flow algorithm for constrained power economic dispatch control. In the proposed algorithm, we consider various constraints such as ower balance, generation capacity, transmission line capacity, transmission losses, security equality, and security inequality constraints. The proposed algorithm consists of four stages. At the first stage, we solve the aggregated problem that is the crude classical economic dispatch problem without considering transmission losses. An initial solution is obtained by the aggregation concept in which the solution satisfies the power balance equations and generation capacity constraints. Then, after load flow analysis, the transmission losses of an initial generation setting are matched by the slack bus generator that produces power with the cheapest cost. At the second stage we consider transmission losses. Formulation of the second stage becomes classical economic dispatch problem involving the transmission losses, which are distributed to all generators. Once a feasible solution is obtained from the second stage, transmission capacity and other violations are checked and corrected locally and quickly at the third stage. The fourth stage fine tunes the solution of the third stage to reach a real minimum. The proposed approach speeds up the two stage optimization method to an average gain of 2.99 for IEEE 30, 57, and 118 bus systems and EPRI Scenario systems A through D testings.

• The Transactions of the Korea Information Processing Society
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• v.3 no.3
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• pp.640-654
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• 1996

This paper presents a synthesis method for multi-level Reed-Muller circuits using BDDs(Binary Decision Diagrams). The existing synthesis tool for Reed circuits, FACTOR, is not appropriate to the synthesis of large circuits because it uses matrix (map-type) to represent given logic functions, resulting in the exponential time and space in number of imput to the circuits. For solving this problems, a syntheisis method based on BDD is presented. Using BDDs, logic functions are represented compactly. Therefor storage spaces and computing time for synthesizing logic functions were greatly decreased, and this technique can be easily applied to large circuits. Using BDD representations, the proposed method extract best patterns to minimize multi-level Reed Muller circuits with good performance in area optimization and testability. Experimental results using the proposed method show better performance than those using previous methods〔2〕. For large circuits of considering the best input partition, synthesis results have been improved.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.1
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• pp.1-6
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• 2020

Fast service access involves keeping track of the location of mobile users, while they are moving around the mobile network for a satisfactory level of QoS (Quality of Service) in a cost-effective manner. The location databases are used to keep track of Mobile Terminals (MT) so that incoming calls can be directed to requested mobile terminals at all times. MT reporting cell system used in location management is to designate each cell in the network as a reporting cell or a non-reporting cell. Determination of an optimal number of reporting cells (or reporting cell configuration) for a given network is reporting cell planning (RCP) problem. This is a difficult combinatorial optimization problem which has an exponential complexity. We can see that a cell in a network is either a reporting cell or a non-reporting cell. Hence, for a given network with N cells, the number of possible solutions is 2^N. We propose a biogeography based optimization (BBO) for design of mobile station location management system in wireless communication network. The number and locations of reporting cells should be determined to balance the registration for location update and paging operations for search the mobile stations to minimize the cost of system. Experimental results show that our proposed BBO is a fairly effective and competitive approach with respect to solution quality for optimally designing location management system because BBO is suitable for combinatorial optimization and multi-functional problems.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.792-797
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• 2011

This paper discusses the application of a hybrid discretiziation method for the discretization procedure that needs to be included in discrete particle swarm optimization (DPSO) for the problem of allocating PV (photovoltaic) systems onto distribution power systems. For this purpose, this paper proposes a rule-based expert system considering the objective function value and its optimizing speed as the input parameters and applied it to the PV allocation problem including discrete decision variables. For multi-level discretization, this paper adopts a hybrid method combined with a simple rounding and sigmoid funtion based 3-step and 5-step quantization methods, and the application of the rule based expert system proposing the adequate discretization method at each PSO iteration so that the DPSO with the hybrid discretization can provide better performance than the previous DPSO.

• Smart Structures and Systems
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• v.17 no.5
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• pp.709-724
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• 2016

This study investigates the optimum design parameters of a superelastic friction base isolator (S-FBI) system through a multi-objective genetic algorithm to improve the performance of isolated buildings against near-fault earthquakes. The S-FBI system consists of a flat steel-PTFE sliding bearing and superelastic NiTi shape memory alloy (SMA) cables. Sliding bearing limits the transfer of shear across the isolation interface and provides damping from sliding friction. SMA cables provide restoring force capability to the isolation system together with additional damping characteristics. A three-story building is modeled with S-FBI isolation system. Multiple-objective numerical optimization that simultaneously minimizes isolation-level displacements and superstructure response is carried out with a genetic algorithm in order to optimize S-FBI system. Nonlinear time history analyses of the building with optimal S-FBI system are performed. A set of 20 near-fault ground motion records are used in numerical simulations. Results show that S-FBI system successfully control response of the buildings against near-fault earthquakes without sacrificing in isolation efficacy and producing large isolation-level deformations.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.7 no.1
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• pp.1-12
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• 1995

In order to seek various relationships among many design parameters employed in the design of the axial-flow fans the program which generates acoustic spectrum has been developed and its validity verified. Outputs of the program, with other outputs from a formerly developed performance prediction program, have been used to form a multi-objective function, for which an optimal design process was carried out. The present analysis shows that overall noise level and efficiency has contrasting trends, and the chord length turns out to be the most critical design variable. In the chosen design case of requirements $Q=2000m^2/min$, ${\Delta}P_s=67mmAq$, D=1.4m, the chord length of 0.2059m minimizes the overall noise level, while chord length of 0.1254m maximizes the efficiency. The resulting chord length in the balanced optimization is 0.1809m.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.109-115
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• 2023

This paper studied the problem of determining the optimal inventory level to meet the customer service target level in a situation where the customer demand for each branch of a nationwide retailer is uncertain. To this end, ISR (In-Stock Ratio) was defined as a key management indicator (KPI) that can be used from the perspective of a nationwide retailer such as Samsung, LG, or Apple that sells goods at branches nationwide. An optimization model was established to allow the retailer to minimize the total amount of inventory held at each branch while meeting the customer service target level defined as the average ISR. This paper proves that there is always an optimal solution in the model and expresses the optimal solution in a generalized form using the Karush-Kuhn-Tucker condition regardless of the shape of the probability distribution of customer demand. In addition, this paper studied the case where customer demand follows a specific probability distribution such as a normal distribution, and an expression representing the optimal inventory level for this case was derived.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2120-2133
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• 2013

In this paper, we address the problem of linear minimum mean-squared error (MMSE) transmitter design for the cognitive radio (CR) multi-user multiple-input single-output (MU-MISO) broadcasting channel (BC), where the cognitive users are subject to not only a sum power constraint, but also a interference power constraint. Evidently, this multi-constraint problem renders it difficult to solve. To overcome this difficulty, we firstly transform it into its equivalent formulation with a single constraint. Then by utilizing BC-MAC duality, the problem of BC transmitter design can be solved by focusing on a dual MAC problem, which is easier to deal with due to its convexity property. Finally we propose an efficient two-level iterative algorithm to search the optimal solution. Our simulation results are provided to corroborate the effectiveness of the proposed algorithm and show that this proposed CR MMSE-based scheme achieves a suboptimal sum-rate performance compared to the optimal DPC-based algorithm with less computational complexity.