• ETRI Journal
• /
• v.46 no.3
• /
• pp.367-378
• /
• 2024

We propose a number-theory-based quantized mathematical optimization scheme for various NP-hard and similar problems. Conventional global optimization schemes, such as simulated and quantum annealing, assume stochastic properties that require multiple attempts. Although our quantization-based optimization proposal also depends on stochastic features (i.e., the white-noise hypothesis), it provides a more reliable optimization performance. Our numerical analysis equates quantization-based optimization to quantum annealing, and its quantization property effectively provides global optimization by decreasing the measure of the level sets associated with the objective function. Consequently, the proposed combinatorial optimization method allows the removal of the acceptance probability used in conventional heuristic algorithms to provide a more effective optimization. Numerical experiments show that the proposed algorithm determines the global optimum in less operational time than conventional schemes.

• Bulletin of the Society of Naval Architects of Korea
• /
• v.25 no.3
• /
• pp.35-45
• /
• 1988

This paper presents a sophisticated Sequential Linear Approximation Method(SLAM) to solve nonlinear optimization problem and the performance of this method is compared with those of the Penalty Function Method(SUMT), Tangent Search Method(TSM) and Flexible Tolerance Method(FTM). To improve the convenience and flexibility in using the proposed SLAM, an user oriented design optimization language is developed and the application examples are shown for the optimization of propeller principal dimensions and the optimization of bulk carrier principal particulars.

• Steel and Composite Structures
• /
• v.23 no.2
• /
• pp.173-186
• /
• 2017

Conceptual configuration and seismic performance of high-rise steel frame-brace structure are studied. First, the topology optimization problem of minimum volume based on truss-like material model under earthquake action is presented, which is solved by full-stress method. Further, conceptual configurations of 20-storey and 40-storey steel frame-brace structure are formed. Next, the 40-storeystructure model is developed in Opensees. Two common configurations are utilized for comparison. Last, seismic performance of 40-storey structure is derived using nonlinear static analysis and nonlinear dynamic analysis. Results indicate that structural lateral stiffness and maximum roof displacement can be improved using brace. Meanwhile seismic damage can also be decreased. Moreover, frame-brace structure using topology optimization is most favorable to enhance lateral stiffness and mitigate seismic damage. Thus, topology optimization is an available way to form initial conceptual configuration in high-rise steel frame-brace structure.

• The Journal of Korea Robotics Society
• /
• v.15 no.3
• /
• pp.212-220
• /
• 2020

This paper deals with a strategy of gain optimization for the kinematic control algorithm of a wire-driven surgical robot. The proposed controller consists of the closed-loop inverse kinematics with the back-calculation method. The closed-loop inverse kinematics has 18 PID control gains, and the back-calculation method has 6 gains. An efficient strategy is designed to optimize 18 values first and then the remaining 6 values. The optimal gain sets are searched under the step input with performance indices. In this gain optimization, the objective function is defined as the minimum value of signal-to-noise ratio of the performance indices for 6 DoF (Degree-of-Freedom) motion that is based on the Taguchi method, and the constraints are applied to obtain stable responses for each motion evenly. The gain sets obtained are verified by simulations using the test trajectories. In comparative results, the optimal gain value based on the performance index combined with ISE (integral of square error) and settling time showed the best control performance.

• Advances in aircraft and spacecraft science
• /
• v.7 no.4
• /
• pp.309-333
• /
• 2020

The proposed study aims to numerically investigate the performance of hydrofoils in the context of amphibious aircraft application. In particular, we also study the effectiveness of a slotted hydrofoil in minimizing the cavitation phenomenon, to improve the overall water take-off performance of an amphibious aircraft. We use the ICON A5 as a base model for this study. First, we propose an approach to estimate the required hydrofoil surface area and to select the most suitable airfoil shape that can minimize cavitation, thus improving the hydrodynamic efficiency. Once the hydrofoil is selected, we perform 2D numerical studies of the hydrodynamic and cavitating characteristics of a non-slotted hydrofoil on ANSYS Fluent. In this work, we also propose to use a slotted hydrofoil to be a passive method to control the cavitation performance through the boundary layer control. Numerical results of several slotted configurations demonstrate notable improvement on the cavitation performance. We then perform a multiobjective optimization with a response surface model to simultaneously minimize the cavitation and maximize the hydrodynamic efficiency of the hydrofoil. The optimization takes the slot geometry, including the slot angle and lengths, as the design variables. In addition, a global sensitivity study has been carried and it shows that the slot widths are the more dominant factors.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.12 no.5
• /
• pp.177-183
• /
• 2012

Cell-phones functions have advanced so rapidly and they are now called 'smart-phones.' Typical approach to optimization the performance of a smartphone is the increasing the speed of device and acquiring more free memory. In this paper, we propose relatively simple techniques that average users can apply to their devices to optimize the performance. For performance upgrade, we proposed an over-clocking technique usually used by computer manufacturers. For memory optimization, we proposed deleting unnecessary apps and replacing with better-functioning apps. We also performed experimentation by applying these techniques to a popular Android phone model and presented the results.

• IE interfaces
• /
• v.20 no.4
• /
• pp.458-468
• /
• 2007

Artificial immune systems (AIS) are one of natural computing inspired by the natural immune system. The fault detection, the pattern recognition, the system control and the optimization are major application area of artificial immune systems. This paper gives a concept of artificial immune systems and useful techniques as like the clonal selection, the immune network theory and the negative selection. A concise survey on the optimization problem based on artificial immune systems is generated. The overall performance of artificial immune systems for the optimization problem is discussed.

• Steel and Composite Structures
• /
• v.42 no.6
• /
• pp.855-864
• /
• 2022

Due to limited resources, and increasing speed of development, the optimal use of available resources has become the most important challenge of human societies. In the last few decades, many researchers have focused their research on solving various optimization problems, providing new optimization methods, and improving the performance of existing optimization methods. Echolocation Search Algorithm (ESA) is an evolutionary optimization algorithm that is based on mimicking the mechanism of the animals such as bats, dolphins, oilbirds, etc in food finding to solve optimization problems. In this paper, the ability of ESA for solving truss size optimization problems with continuous variables is investigated. To examine the efficiency of ESA, three benchmark examples are considered. The numerical results exhibit the effectiveness of ESA for solving truss optimization problems.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.4 no.4
• /
• pp.575-594
• /
• 2010

In this study, we propose a space search algorithm (SSA) and then introduce a hybrid optimization of fuzzy inference systems based on SSA and information granulation (IG). In comparison with "conventional" evolutionary algorithms (such as PSO), SSA leads no.t only to better search performance to find global optimization but is also more computationally effective when dealing with the optimization of the fuzzy models. In the hybrid optimization of fuzzy inference system, SSA is exploited to carry out the parametric optimization of the fuzzy model as well as to realize its structural optimization. IG realized with the aid of C-Means clustering helps determine the initial values of the apex parameters of the membership function of fuzzy model. The overall hybrid identification of fuzzy inference systems comes in the form of two optimization mechanisms: structure identification (such as the number of input variables to be used, a specific subset of input variables, the number of membership functions, and polyno.mial type) and parameter identification (viz. the apexes of membership function). The structure identification is developed by SSA and C-Means while the parameter estimation is realized via SSA and a standard least square method. The evaluation of the performance of the proposed model was carried out by using four representative numerical examples such as No.n-linear function, gas furnace, NO.x emission process data, and Mackey-Glass time series. A comparative study of SSA and PSO demonstrates that SSA leads to improved performance both in terms of the quality of the model and the computing time required. The proposed model is also contrasted with the quality of some "conventional" fuzzy models already encountered in the literature.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.23 no.1
• /
• pp.37-43
• /
• 2010

In this paper, a reliability-based design optimization is developed for the topology design of linear structures using a performance measure approach. Spatial domain is discretized using three dimensional Reissner-Mindlin plate elements and design variable is taken as the material property of each element. A continuum based adjoint variable method is employed for the efficient computation of sensitivity with respect to the design and random variables. The performance measure approach of RBDO is employed to evaluate the probabilistic constraints. The topology optimizationproblem is formulated to have probabilistic displacement constraints. The uncertainties such as material property and external loads are considered. Numerical examples show that the developed topology optimization method could effectively yield a reliable design, comparing with the other methods such as deterministic, safety factor, and worst case approaches.