• Proceedings of the KSME Conference
• /
• 2007.05a
• /
• pp.572-577
• /
• 2007

The paper presents design optimization of an automobile body for dynamic stiffness improvement. The thicknesses of plates making-up the monocoque body of an automobile were employed as design variables for optimization and the objective was to increase the first torsional and bending natural frequencies. By allotting one design variable to each plate of the body, compared to previous works based on element-wise design variables, design space of optimization was reduced to a large extent and numerical instabilities such as checkerboard pattern was efficiently evaded. The method resulted to a considerable amount of increase in the automobile body's torsional and bending natural frequencies. Considering manufacturability of the optimized result, the converged values of plate thicknesses were approximated to commercially-available values by appropriately reflecting their design sensitivities.

• Journal of Microbiology and Biotechnology
• /
• v.14 no.6
• /
• pp.1163-1169
• /
• 2004

An unstructured mathematical model is presented for lactic acid fermentation based on the energy balance. The proposed model reflects the energy metabolic state and then predicts the cell growth, lactic acid production, and glucose consumption rates by relating the above rates with the energy metabolic rate. Fermentation experiments were conducted under various initial lactic acid concentrations of 0, 30, 50, 70, and 90 g/l. Also, a genetic algorithm was used for further optimization of the model parameters and included the operations of coding, initialization, hybridization, mutation, decoding, fitness calculation, selection, and reproduction exerted on individuals (or chromosomes) in a population. The simulation results showed a good fit between the model prediction and the experimental data. The genetic algorithm proved to be useful for model parameter optimization, suggesting wider applications in the field of biological engineering.

• Journal of Korean Institute of Industrial Engineers
• /
• v.33 no.4
• /
• pp.447-456
• /
• 2007

The ant colony optimization (ACO) is a probabilistic Meta-heuristic algorithm which has been developed in recent years. Originally ACO was used for solving the well-known Traveling Salesperson Problem. More recently, ACO has been used to solve many difficult problems. In this paper, we develop an ant colony optimization method to solve the maximum independent set problem, which is known to be NP-hard. In this paper, we suggest a new method for local information of ACO. Parameters of the ACO algorithm are tuned by evolutionary operations which have been used in forecasting and time series analysis. To show the performance of the ACO algorithm, the set of instances from discrete mathematics and computer science (DIMACS)benchmark graphs are tested, and computational results are compared with a previously developed ACO algorithm and other heuristic algorithms.

• Journal of Electrical Engineering and Technology
• /
• v.12 no.4
• /
• pp.1417-1426
• /
• 2017

Power system analysis, Non-Convex Economic Dispatch (NED) is considered as an open and demanding optimization problem. Despite the fact that realistic ED problems have non-convex cost functions with equality and inequality constraints, conventional search methods have not been able to effectively find the global answers. Considering the great potential of meta-heuristic optimization techniques, many researchers have started applying these techniques in order to solve NED problems. In this paper, a new and efficient approach is proposed based on imperialist competitive algorithm (ICA). The proposed algorithm which is named multi-operator ICA (MuICA) merges three operators with the original ICA in order to simultaneously avoid the premature convergence and achieve the global optimum answer. In this study, the proposed algorithm has been applied to different test systems and the results have been compared with other optimization methods, tending to study the performance of the MuICA. Simulation results are the confirmation of superior performance of MuICA in solving NED problems.

• Structural Engineering and Mechanics
• /
• v.58 no.2
• /
• pp.301-326
• /
• 2016

An optimization method of patch shape was developed in this study, in order to improve repair of cracked plates. It aimed to minimize three objectives: stress intensity factor, patch volume and shear stresses in the adhesive film. The choice of these objectives ensures improving crack repair, gaining mass and enhancing the adhesion durability between the fractured plate and the composite patch. This was a multi-objective optimization combined with Finite elements calculations to find out the best distribution of patch height with respect to its width. The implementation of the method identified families of optimal shapes with specific geometric features around the crack tip and at the horizontal end of the patch. Considerable mass gain was achieved while improving the repair efficiency and keeping the adhesive shear stress at low levels.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.1 no.1
• /
• pp.6-12
• /
• 2001

Evolutionary algorithms(EAs) have been successfully applied to many combinatorial optimization problems of various engineering fields. Recently, some comparative studies of EAs with other stochastic search algorithms have, however, shown that they are similar to, or even are not comparable to other heuristic search. In this paper, a new hybrid evolutionary algorithm utilizing a new local heuristic search, for combinatorial optimization problems, is presented. The new intelligent local heuristic search is described, and the behavior of the hybrid search algorithm is investigated on two well-known problems: traveling salesman problems (TSPs), and quadratic assignment problems(QAPs). The results indicate that the proposed hybrid is able to produce solutions of high quality compared with some of evolutionary and simulated annealing.

• 한국전산유체공학회:학술대회논문집
• /
• 2003.10a
• /
• pp.237-239
• /
• 2003

The present study investigates on design optimization of rib-roughened two-dimensional channel to enhance turbulent heat transfer. Response surface method with Reynolds-averaged Navier-Stokes analysis is used as an optimization technique. Standard $k-{\varepsilon}$model with wall functions is adopted as a turbulence closure. The objective function is defined as a linear combination of heat transfer and friction drag coefficients with weighting factor. Computational results for overall heat transfer rate show good agreements with experimental data. Four design variables are optimized for weighting factor of 0.02.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2000.11a
• /
• pp.381-384
• /
• 2000

Multi-disciplinary optimization design concept can provide a solution to many engineering problems. In the field of structural analysis, much development of size or topology optimization has been achieved in the application of research. This paper demonstrates an optimum design of a multi-layer cylindrical tube which behaves thermoelastically. A multi-layer cylindrical tube that has several different material properties at each layer is optimized within allowable stress and temperature range when mechanical and thermal loads are applied simultaneously. To analyze these problems using an efficient and precise method, the optimization theories are adopted to perform thermoelastic finite element analysis.

• Structural Engineering and Mechanics
• /
• v.57 no.4
• /
• pp.763-783
• /
• 2016

A methodology based on Teaching Learning-Based Optimization (TLBO) algorithm is proposed for optimum design of reinforced concrete retaining walls. The objective function is to minimize total material cost including concrete and steel per unit length of the retaining walls. The requirements of the American Concrete Institute (ACI 318-05-Building code requirements for structural concrete) are considered for reinforced concrete (RC) design. During the optimization process, totally twenty-nine design constraints composed from stability, flexural moment capacity, shear strength capacity and RC design requirements such as minimum and maximum reinforcement ratio, development length of reinforcement are checked. Comparing to other nature-inspired algorithm, TLBO is a simple algorithm without parameters entered by users and self-adjusting ranges without intervention of users. In numerical examples, a retaining wall taken from the documented researches is optimized and the several effects (backfill slope angle, internal friction angle of retaining soil and surcharge load) on the optimum results are also investigated in the study. As a conclusion, TLBO based methods are feasible.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.15 no.26
• /
• pp.67-76
• /
• 1992

변수의 어떤 값들에 대해 도함수를 가질 수 없는 함수를 최적화해야 하는 등. OR 에서는 여러 상황이 존재한다. 이것은 Convex Analysis〔12〕서 이론적인 differential calculus를 근저로 하는 Non-differentiable Optimization 또는 Non-smooth Optimization 을 취급하는 것이 된다. 이러한 종류의 미분이 가능하지 않은 최적화문제는 연속함수를 위한 종래의 최적화법으로는 그 해법자체가 갖고 있는 연속성의 한계를 극복할 수 없다. 따라서, 이러한 문제를 해결하기 위해 Demyanov〔4〕가 제시한 quasi-differental function의 정의와 이들 함수에 따른 몇가지 주요정리들을 언급하고, 그것들을 토대로 Non-differentiable optimization problem의 수치적인 방법을 수행하기 위해 일종의 modified gradient 법을 제시한다. 이를 이용해서 numerical experiment를 위한 방법을 구체화하여, unrestricted non-differentable optimization problem에 적응하여, 그 수치해 결과를 보여서 그 타당성음 검토하였다.