• Advances in Computational Design
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• v.5 no.3
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• pp.209-231
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• 2020

In order to evaluate the performance of three heuristic optimization algorithms, namely, simulated annealing (SA), genetic algorithm (GA) and particle swarm optimization (PSO) for optimal stacking sequence of laminated composite plates with respect to critical buckling load and non-dimensional natural frequencies, a multi-objective optimization procedure is developed using the weighted summation method. Classical lamination theory and first order shear deformation theory are employed for critical buckling load and natural frequency computations respectively. The analytical critical buckling load and finite element calculation schemes for natural frequencies are validated through the results obtained from literature. The comparative study takes into consideration solution and computational time parameters of the three algorithms in the statistical evaluation scheme. The results indicate that particle swarm optimization (PSO) considerably outperforms the remaining two methods for the special problem considered in the study.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2005.10a
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• pp.277-280
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• 2005

A shape optimization is applied to achieve a design objective in three-dimensional forging processes. In multi-stage forging processes, among the important design aspects, the die shape fur preforming is regarded as the design variable since it influences the forged part relatively higher than the others. The rigid-plastic finite element method and the sensitivity method are employed and formulated to solve a formulated optimization problem. An approximation scheme is also used for the direction search during the optimization. The upset forging of a square box is selected as a test example in order to demonstrate and verify the optimization process of this study. After the optimization, the optimized shape of the die yields a finial product of desire shape.

• Korean Institute of Interior Design Journal
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• no.29
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• pp.86-93
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• 2001

This study presents about the method of alternatives selection by considering wall performance and interior design. Wall is selected fur the object and 3 items of cost, performance, and design as the objective function for optimizing are determined. Thus the wall performance selected problems, which are improvement of insulation performance, sweaty prevention, sound insulation performance and design selected problems, which is satisfactory Improvement of users about Interior design. It is important to select alternatives that can satisfy the performance and design on the capital given as much as possible. But quantitative problem such as performance or expanses and qualitative problem such as design are not in the same dimension. Therefore this problem is a multi-criteria optimization problem and also has used AHP method as the method to solve these. Moreover GA is used to solve a problem of the alternatives occurrence, which is the characteristic of multi-criteria problem. This study presents the solution method on multi-criteria problem that has been mix loaded of quantitative problem and qualitative problem by using AHP(Analytic Hierarchy Process) and GA(Genetic Algorithm).

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.4
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• pp.28-33
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• 2015

In this study, the optimal design for the support and the binding device for the protection of crops for the maximum allowable stress of the shape necessary to minimize volume has been proposed. Optimization of the support and the binding device for the crops should be designed to support businesses in terms of profit, in part to reduce the material, and to profit from the ease and speed of working that part of the farmers. We used CATIA for the mechanical design and the ANSYS program for the structural analysis. Additionally, the optimization was performed by PIAnO with seven design variables for the binding device and three parameters for the support. The weight method using a multi-objective function was also determined by the Pareto optimal solution. The volume of the binding device in the optimum design result was found to be reduced by 16%, from $2.278e-005m^3to1.912e-005m^3$. From the result, we confirmed the effectiveness of the design method proposed as a multi-objective function optimization problem.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1586-1595
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• 2018

For the problem that the complexity of 3-D modeling and multi parameter optimization, as well as the uncertainty of the winding factor of axial flux permanent magnet generator with coreless windings. The complex 3-D model was simplified into 2-D analytic model, and an analytical formula for the winding factor that adapting different coreless stator winding is proposed in this paper. The analytical solution for air-gap magnetic fields, no-load back EMF, electromagnetic torque, and efficiency are calculated by using this method. The multiple objective and multivariable optimization of the maximum fundamental and the minimum harmonic content of back EMF are performed by using response surface methodology. The proposed optimum design method was applied to make a generator. The generator was tested and the calculated results are compared with the proposed method, which show good agreements.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.2
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• pp.107-114
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• 2024

Mobile ad hoc networks represent self-configuring networks of mobile devices that communicate without relying on a fixed infrastructure. However, traditional routing protocols in such networks encounter challenges in selecting efficient and reliable routes due to dynamic nature of these networks caused by unpredictable mobility of nodes. This often results in a failure to meet the low-delay and low-energy consumption requirements crucial for such networks. In order to overcome such challenges, our paper introduces a novel multi-objective and adaptive routing scheme based on the Q-learning reinforcement learning algorithm. The proposed routing scheme dynamically adjusts itself based on measured network states, such as traffic congestion and mobility. The proposed approach utilizes Q-learning to select routes in a decentralized manner, considering factors like energy consumption, load balancing, and the selection of stable links. We present a formulation of the multi-objective optimization problem and discuss adaptive adjustments of the Q-learning parameters to handle the dynamic nature of the network. To speed up the learning process, our scheme incorporates informative shaped rewards, providing additional guidance to the learning agents for better solutions. Implemented on the widely-used AODV routing protocol, our proposed approaches demonstrate better performance in terms of energy efficiency and improved message delivery delay, even in highly dynamic network environments, when compared to the traditional AODV. These findings show the potential of leveraging reinforcement learning for efficient routing in ad hoc networks, making the way for future advancements in the field of mobile ad hoc networking.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.89-96
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• 2018

When a fault occurs in a power system, the existing analytic models for the power system fault diagnosis could generate multiple solutions under the condition of one or more protective relays (PRs) and/or circuit breakers (CBs) malfunctioning, and/or an alarm or alarms of these PRs and/or CBs failing. Therefore, this paper presents an improved analytic model addressing the above problem. It takes into account the interaction between the uncertainty involved with PR operation and CB tripping and the uncertainty of the alarm reception, which makes the analytic model more reasonable. In addition, the existing analytic models apply the penalty function method to deal with constraints, which is influenced by the artificial setting of the penalty factor. In order to avoid the penalty factor's effects, this paper transforms constraints into an objective function, and then puts forward an improved immune clonal multi-objective optimization algorithm to solve the optimal solution. Finally, the cases of the power system fault diagnosis are served for demonstrating the feasibility and efficiency of the proposed model and method.

• Korean Management Science Review
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• v.32 no.4
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• pp.69-80
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• 2015

The semiconductor industry is one of those in which the most intricate processes are involved and there are many critical factors that are controlled with precision in those processes. Naturally production scheduling in the semiconductor industry is also very complex and studied by the industry and academia for many years; however, still there are many issues left unclear in the problem. This paper proposes an multi-objective optimization-based scheduling method for semiconductor fabrication(fab). Two main objectives are throughput maximization and meeting target production quantities. The first objective aims to reduce production cost, especially the fixed cost incurred by a large investment constructing a new fab facility. The other is meeting customer orders on time and also helps a fab maintain stable throughput through controlled WIP balancing in the long run. The paper shows a trade-off structure between the two objectives through experimental studies, which provides industrial practitioners with useful references.

• Proceeding of EDISON Challenge
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• 2016.03a
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• pp.455-462
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• 2016

Recently, followed by rapid growth of robotics field, multi-linkage mechanism which can even pass by rough road is getting lots of attention. In this paper, I focused on Jansen mechanism. It's a kinematics object which is named after Dutch artist Theo jansen. Jansen mechanism embraces structure and mechanism which creates locomotion with the combination of the power and simple structure. Theo jansen suggests a 'Holy number'. It's an ideal ratio of leg components length. However, if there's desired gait locomotion, you have to adjust the ratio and the length. But even slight change of the length could cause a big change at the end-point. To solve this problem, I suggest a reverse engineering method to get a ratio of each links by nonlinear optimization with pre-set desired trajectory. First, we converted a movement of the joint of Jansen mechanism to vectors by kinematics analysis of multi-linkage structure. And we showed the trajectory at the end-point. After that, we set desired trajectory which we found most ideal. Then we got the length of the leg components which draws a trajectory as same as trajectory we set, using Multi-objective genetic algorithm toolbox in MATLAB. Result is verified by Edison designer and mSketch. And we analyzed if it could pass through the obstruction which is set dynamically.

• Journal of the Semiconductor & Display Technology
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• v.20 no.4
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• pp.38-43
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• 2021

Permanent magnet linear synchronous motor (PMLSM) is suitable for use in cleanroom environments and have advantages such as high speed, high thrust, and high precision. If the stators are arranged in the entire moving path of the mover, there is a problem in that the installation cost increases. To solve this problem, discontinuous armature arrangement PMLSM has been proposed. In this case, the mover receives a greater detent force in the section where the stator is not arranged. When a large detent force occurs, it appears as a ripple component of the thrust during PMLSM operation. If the shape of the stator is changed to reduce the detent force, the characteristics of the back EMF are changed. Therefore, in this paper, the detent force and the harmonic components of back EMF were reduced through multi-purpose shape optimization. To this end, the FEA model was constructed and main effect analysis was performed on the major shape variables affecting each objective function. Then, the optimal shape that minimizes the objective function was derived through the response surface analysis method.