• Journal of Information Processing Systems
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• v.14 no.5
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• pp.1237-1253
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• 2018

Harmony search algorithm is an emerging meta-heuristic optimization algorithm, which is inspired by the music improvisation process and can solve different optimization problems. In order to further improve the performance of the algorithm, this paper proposes an improved harmony search algorithm. Key parameters including harmonic memory consideration (HMCR), pitch adjustment rate (PAR), and bandwidth (BW) are optimized as the number of iterations increases. Meanwhile, referring to the genetic algorithm, an improved method to generate a new crossover solutions rather than the traditional mechanism of improvisation. Four complex function optimization and pressure vessel optimization problems were simulated using the optimization algorithm of standard harmony search algorithm, improved harmony search algorithm and exploratory harmony search algorithm. The simulation results show that the algorithm improves the ability to find global search and evolutionary speed. Optimization effect simulation results are satisfactory.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.359-361
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• 2015

We use the millennium simulation for studying the evolution of groups of galaxies over time. We find fossil and non-fossil groups as well as old and young groups at redshift z = 0 and follow them back in time to investigate the evolution of their parameters, such as mass assembly, luminosity gap and halo mass concentration. We find that fossils assemble a larger fraction of their mass at z = 0 than controls. The magnitude gaps between fossil and non-fossil groups are not the same because of major and minor mergers, in old and young groups as well. We also find that WMAP1 and WMAP7 cosmologies lead to the same evolutionary history for fossil and control groups.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.473-474
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• 2015

Halo merger trees are the essential backbone of semi-analytic models for galaxy formation and evolution. Srisawat et al. (2013) show that different tree building algorithms can build different halo merger histories from a numerical simulation for structure formation. In order to understand the differences induced by various tree building algorithms, we investigate the impact of halo merger trees on a semi-analytic model. We find that galaxy properties in our models show differences between trees when using a common parameter set. The models independently calibrated for each tree can reduce the discrepancies between global galaxy properties at z=0. Conversely, with regard to the evolutionary features of galaxies, the calibration slightly increases the differences between trees. Therefore, halo merger trees extracted from a common numerical simulation using different, but reliable, algorithms can result in different galaxy properties in the semi-analytic model. Considering the uncertainties in baryonic physics governing galaxy formation and evolution, however, these differences may not necessarily be significant.

• Journal of information and communication convergence engineering
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• v.3 no.1
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• pp.43-48
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• 2005

In this paper, the adaptive fuzzy logic controller(AFLC) is proposed, which uses real-coding genetic algorithm showing a good performance on convergence velocity and diversity of population among evolutionary computations. The effectiveness of the proposed AFLC was demonstrated by computer simulation for speed control system of AC servo motor. As a result of simulation for the AC servo motor, it is shown the proposed AFLC has the better performance on overshoot, settling time and rising time than the PI controller which is used when tuning AFLC.

• Smart Structures and Systems
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• v.26 no.6
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• pp.797-807
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• 2020

Due to the influence of nonlinearity and time-variation, it is difficult to establish an accurate model of concrete frame structures that adopt active controllers. Fuzzy theory is a relatively appropriate method but susceptible to human subjective experience to decrease the performance. This paper proposes a novel artificial intelligence based EBA (Evolved Bat Algorithm) controller with machine learning matched membership functions in the complex nonlinear system. The proposed affine transformed membership functions are adopted and stabilization and performance criterion of the closed-loop fuzzy systems are obtained through a new parametrized linear matrix inequality which is rearranged by machine learning affine matched membership functions. The trajectory of the closed-loop dithered system and that of the closed-loop fuzzy relaxed system can be made as close as desired. This enables us to get a rigorous prediction of stability of the closed-loop dithered system by establishing that of the closed-loop fuzzy relaxed system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.683-688
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• 2018

Recently, the demand for electric energy has been increasing due to the spread of hybrid electric vehicles. In this study, to meet this demand, the ANSYS MAXWELL electromagnetic simulation system was used to compare the power generation characteristics of three types of suspension system that can generate electricity using energy harvesting technology. Next, the optimal design was determined for each model by using the commercial PIDO (Process Integration and Design Optimization) tool, PIANO (Process Integration, Automation and Optimization). We selected three design variables and constructed an approximate model based on the experimental design method through electromagnetic analysis for 18 experimental points derived from Orthogonal Arrays among the experimental design methods. Then, we determined the optimal design by applying the Evolutionary Algorithm. Finally, the optimal design results were verified by electromagnetic simulation of the optimum design result model using the same analysis conditions as those of the initial model. After comparing the power generation characteristics for the optimal structure for each linear generator model, the maximum power generation amounts in the 8pole-8slot, 12pole-12slot, and 16pole-16slot structures were 366.5W, 466.7W and 579.7W, respectively, and it was found that as the number of slots and poles increases, the power generation increases.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.169-178
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• 2010

Agent based simulation is an approach for the analysis of a system's long term behavior where the entities in the system behave independently by their own judgement and memory, but influence each other to cope with given environment. In this paper we developed an agent based simulation model for the analysis of behavioral mechanism of team formation. In the process of team formation members' mutual preference is an important factor although each member can join up with one's own will. Also a team performance can vary by the member's own experience. We implemented the developed model using Netlogo 4.1, and verified the model by simulation. From the simulation results we found that the model successfully performed necessary functions using behavioral rules, judgments, and evolutionary processes by memory. As a further study we will be able to apply the model for analyzing various ecological behavior of team formation.

• Journal of the Korea Society for Simulation
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• v.22 no.2
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• pp.33-40
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• 2013

This paper explores a border security system based on agent-based modeling and simulation (ABMS). The ABMS software platform, map aware non-uniform automata, is used to model various scenarios and evaluate the border security system given a set of infiltrators who have evolutionary behavior governed by genetic algorithm (GA). we formulated an optimization model and approximately solved it using a GA in order to capture near optimal behavior of an infiltrating force. The results presented give two significant insights for our border security system in that optimizing the infiltrator's behavior can make a significant difference and the quantitative results regarding the infiltrator's avoidance of each asset can be viewed as capturing their relative importance.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.330-336
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• 2014

Many industrial processes such as continuous stirred tank reactors(CSTRs), desalination plant, distillation columns, pH neutralization processes and so on exhibit highly nonlinear characteristic and time-varying behavior during operation. The control of such processes has been challenging to control engineers. Hence, a variety of forms of PID controllers and their tuning rules for industrial processes have been developed to guarantee the best performance. In this paper, a scheme that designs the practical PID controller with an anti-windup strategy incorporating with an evolutionary algorithm(EA) is presented for the concentration control of a nonisothermal CSTR. EA is used to tune the parameters of the overall PID control process with anti-windup by minimizing the integral of absolute error(IAE). Simulation works for reference tracking and disturbance rejecting performances and robustness to parameter changes show the feasibility of using the proposed method.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2011.06a
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• pp.218-219
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• 2011

This paper focuses on dispatching strategy for AGVs(Automated Guided Vehicle). The goal of AGV dispatching problem is allocating jobs to AGVs to minimizing QC delay and AGV total travel distance. Due to the highly dynamic nature of container terminal environment, the effect of dispatching is hard to predict thus it leads to frequent modification of dispatching results. Given this situation, single rule-based approach is widely used due to its simplicity and small computational cost. However, single rule-based approach has a limitation that cannot guarantee a satisfactory performance for the various performance measures. In this paper, dispatching strategy based on multicriteria heuristics is proposed. Proposed strategy consists of multiple decision criteria. A muti-objective evolutionary algorithm is applied to optimize weights of those criteria. The result of simulation experiment shows that the proposed approach outperforms single rule-based dispatching approaches.