• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.175-178
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• 2003

In recent years, several researchers have presented the extensive research reports on network optimization problems. In our real life applications, many important network problems are typically formulated as a Maximum flow model (MXF) or a Minimum Cost flow model (MCF). In this paper, we propose a Genetic Algorithm (GA) approach used a priority-based chromosome for solving the bicriteria network optimization problem including MXF and MCF models(MXF/MCF).

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.40-48
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• 2021

Content-Based Image Retrieval (CBIR) system plays a vital role to retrieve the relevant images as per the user perception from the huge database is a challenging task. Images are represented is to employ a combination of low-level features as per their visual content to form a feature vector. To reduce the search time of a large database while retrieving images, a novel image retrieval technique based on feature dimensionality reduction is being proposed with the exploit of metaheuristic optimization techniques based on Genetic Algorithm (GA), Extended Binary Cuckoo Search (EBCS) and Whale Optimization Algorithm (WOA). Each image in the database is indexed using a feature vector comprising of fuzzified based color histogram descriptor for color and Median binary pattern were derived in the color space from HSI for texture feature variants respectively. Finally, results are being compared in terms of Precision, Recall, F-measure, Accuracy, and error rate with benchmark classification algorithms (Linear discriminant analysis, CatBoost, Extra Trees, Random Forest, Naive Bayes, light gradient boosting, Extreme gradient boosting, k-NN, and Ridge) to validate the efficiency of the proposed approach. Finally, a ranking of the techniques using TOPSIS has been considered choosing the best feature selection technique based on different model parameters.

• Journal of Korean Society of Steel Construction
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• v.18 no.2
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• pp.147-160
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• 2006

GA-based fuzzy optimum design algorithm incorporated with the refined plastic hinge analysis method is presented in this study. In the refined plastic hinge analysis method, geometric nonlinearity is considered by using the stability functions of the beam-column members. Material nonlinearity is also considered by using the gradual stiffness degradation model, which considers the effects of residual stresses, moment redistribution through the occurence of plastic hinges, and the geometric imperfections of the members. In the genetic algorithm, the tournament selection method and the total weight of the steel frames. The requirements of load-carrying capacity, serviceability, ductility, and constructabil ity are used as the constraint conditions. In fuzzy optimization, for crisp objective function and fuzzy constraint s, the tolerance that is accepted is 5% of the constraints. Furthermore, a level-cut method is presented from 0 to 1 at a 0 .2 interval, with the use of the nonmembership function, to solve fuzzy-optimization problems. The values of conventional GA optimization and fuzzy GA optimization are compared in several examples of steel structures.

• Computers and Concrete
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• v.6 no.3
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• pp.253-268
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• 2009

This study aims to develop a cost-based high-performance concrete (HPC) mix optimization system based on an integrated approach using artificial neural networks (ANNs) and genetic algorithms (GA). ANNs are used to predict the three main properties of HPC, namely workability, strength and durability, which are used to evaluate fitness and constraint violations in the GA process. Multilayer back-propagation neural networks are trained using the results obtained from experiments and previous research. The correlation between concrete components and its properties is established. GA is employed to arrive at an optimal mix proportion of HPC by minimizing its total cost. A system prototype, called High Performance Concrete Mix-Design System using Genetic Algorithm and Neural Networks (HPCGANN), was developed in MATLAB. The architecture of the proposed system consists of three main parts: 1) User interface; 2) ANNs prediction models software; and 3) GA engine software. The validation of the proposed system is carried out by comparing the results obtained from the system with the trial batches. The results indicate that the proposed system can be used to enable the design of HPC mix which corresponds to its required performance. Furthermore, the proposed system takes into account the influence of the fluctuating unit price of materials in order to achieve the lowest cost of concrete, which cannot be easily obtained by traditional methods or trial-and-error techniques.

• Journal of Satellite, Information and Communications
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• v.6 no.1
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• pp.6-11
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• 2011

In this paper presents a new approach to evaluate reliability indices of electric distribution systems using genetic Algorithm (GA). The use of reliability evaluation is an important aspect of distribution system planning and operation to adjust the reliability level of each area. In this paper, the reliability model is based on the optimal load transferring problem to minimize load generated load point outage in each sub-section. This approach is one of the most difficult procedures and become combination problems. A new approach using GA was developed for this problem. GA is a general purpose optimization technique based on principles inspired from the biological evolution using metaphors of mechanisms such as natural selection, genetic recombination and survival of the fittest. Test results for the model system with 24 nodes 29 branches are reported in the paper.

• Journal of Mechanical Science and Technology
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• v.16 no.8
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• pp.1033-1038
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• 2002

Genetic alsorithm (GA) , compared to the gradient-based optimization, has advantages of convergence to a global optimized solution. The genetic algorithm requires so many number of analyses that may cause high computational cost for genetic search. This paper proposes a personal computer network programming based on TCP/IP protocol and client-server model using socket, to improve processing speed of the genetic algorithm for optimization of composite laminated structures. By distributed processing for the generated population, improvement in processing speed has been obtained. Consequently, usage of network-based genetic algorithm with the faster network communication speed will be a very valuable tool for the discrete optimization of large scale and complex structures requiring high computational cost.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2146-2148
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• 2002

In this paper, PID control method using genetic algorithm to control the nonlinear multivariable system is presented. Genetic algorithms are global search techniques for nonlinear optimization. For experiment, the x-y rod balancing system with driver circuit board is fabricated. Experiments such as angle and position control for system are performed. The validity and control performance of the GA-based PID controller are confirmed by experimental results.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.114-116
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• 2015

This paper presents a Stochastic Time-Cost Tradeoff analysis system (STCT) that identifies optimal construction methods for activities, hence reducing the project completion time and cost simultaneously. It makes use of schedule information obtained from critical path method (CPM), applies alternative construction methods data obtained from estimators to respective activities, computes an optimal set of genetic algorithm (GA) parameters, executes simulation based GA experiments, and identifies near optimal solution(s). A test case verifies the usability of STCT.

• Electronic Materials Letters
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• v.14 no.6
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• pp.784-792
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• 2018

In this letter, a standard deviation based optimization technique has been applied on High Resolution X-ray Diffraction symmetric and asymmetric scan results to accurately determine the Aluminum molar fraction and lattice relaxation of Molecular Beam Epitaxy grown compositionally graded Aluminum Gallium Nitride (AlGaN)/Aluminum Nitride/Gallium Nitride (GaN) heterostructures. Mathews-Blakeslee critical thickness model has been applied in an alternative way to determine the partially relaxed AlGaN epilayer thicknesses. The coupling coefficient determination has been presented in a different perspective involving sample tilt method by off set between the asymmetric planes of GaN and AlGaN. Sample tilt is further increased to determine mosaic tilt ranging between $0.01^{\circ}$ and $0.1^{\circ}$.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.3
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• pp.409-422
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• 2016

A parametric study based on an unsteady mathematical model of a pyrotechnically actuated device was performed for design optimization. The model simulates time histories for the chamber pressure, temperature, mass transfer and pin motion. It is validated through a comparison with experimentally measured pressure and pin displacement. Parametric analyses were conducted to observe the detailed effects of the design parameters using a validated performance analysis code. The detailed effects of the design variables on the performance were evaluated using the one-at-a-time (OAT) method, while the scatter plot method was used to evaluate relative sensitivity. Finally, the design optimization was conducted by employing a genetic algorithm (GA). Six major design parameters for the GA were chosen based on the results of the sensitivity analysis. A fitness function was suggested, which included the following targets: minimum explosive mass for the uniform ignition (small deviation), light casing weight, short operational time, allowable pyrotechnic shock force and finally the designated pin kinetic energy. The propellant mass and cross-sectional area were the first and the second most sensitive parameters, which significantly affected the pin's kinetic energy. Even though the peak chamber pressure decreased, the pin kinetic energy maintained its designated value because the widened pin cross-sectional area induced enough force at low pressure.