• The Journal of Asian Finance, Economics and Business
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• 제2권2호
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• pp.13-18
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• 2015

In this paper the DRC model is presented for solving multi objective problem. The proposed model is a combination of data envelopment analysis, Cuckoo algorithm and the response surface method. Due to reasons like costs, time and irreversible damages, it is not possible to analyze each and every one of the proposed models in practice, so the simulation is used. Since the number of experiments for simulation process is high then the optimization has gone to practice and directs the simulation process. The response surface method is used as one of the approaches of simulation optimization. Furthermore, data envelopment analysis is used to consider several response surfaces as efficiency response surface. Then this efficiency response surface is solved by Cuckoo algorithms. The main advantage of DRC model is to make one efficiency response surface function instate of multi surface function for every output and also using the advantages of Cuckoo algorithms. In order to demonstrate the effectiveness of the proposed approach, the branches of Refah bank in Mashhad is analyzed and the results are presented.

• Journal of Navigation and Port Research
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• 제32권10호
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• pp.829-835
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• 2008

The objective of this study is to present the two-step dispatching strategy for the purpose of the transport vehicle with multi-function used in container terminal. The two-step dispatching is a method to save the waiting time between transport vehicle and cranes using real time location control. The first step dispatching is to allocate the destination location based on the real time location information. The second step dispatching is to indicate the specific job such as loading, unloading, and pick-up based on the condition of working area. This two-step dispatching strategy decreases the waiting times of the stevedoring system and will contribute at a productivity improvement in container terminal.

• Journal of Auto-vehicle Safety Association
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• 제11권3호
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• pp.30-36
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• 2019

This paper suggests a car-following algorithm for urban environment, with multiple target candidates. Until now, advanced driver assistant systems (ADASs) and self-driving technologies have been researched to cope with diverse possible scenarios. Among them, car-following driving has been formed the groundwork of autonomous vehicle for its integrity and flexibility to other modes such as smart cruise system (SCC) and platooning. Although the field has a rich history, most researches has been focused on the shape of target trajectory, such as the order of interpolated polynomial, in simple single-lane situation. However, to introduce the car-following mode in urban environment, realistic situation should be reflected: multi-lane road, target's unstable driving tendency, obstacles. Therefore, the suggested car-following system includes both in-lane preceding vehicle and other factors such as side-lane targets. The algorithm is comprised of three parts: path candidate generation and optimal trajectory selection. In the first part, initial guesses of desired paths are calculated as polynomial function connecting host vehicle's state and vicinal vehicle's predicted future states. In the second part, final target trajectory is selected using quadratic cost function reflecting safeness, control input efficiency, and initial objective such as velocity. Finally, adjusted path and control input are calculated using model predictive control (MPC). The suggested algorithm's performance is verified using off-line simulation using Matlab; the results shows reasonable car-following motion planning.

• Journal of the Earthquake Engineering Society of Korea
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• 제12권6호
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• pp.13-23
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• 2008

In this study, a finite element (FE) model updating method based on the hybrid genetic algorithm (HGA) is proposed to improve the grillage FE model for plate girder bridges. HGA consists of a genetic algorithm (GA) and direct search method (DS) based on a modification of Nelder & Mead's simplex optimization method (NMS). Fitness functions based on natural frequencies, mode shapes, and static deflections making use of the measurements and analytical results are also presented to apply in the proposed method. In addition, a multi-objective function has been formulated as a linear combination of fitness functions in order to simultaneously improve both stiffness and mass. The applicability of the proposed method to girder bridge structures has been verified through a numerical example on a two-span continuous grillage FE model, as well as through an experimental test on a simply supported plate girder skew bridge. In addition, the effect of measuring error is considered as random noise, and its effect is investigated by numerical simulation. Through numerical and experimental verification, it has been proven that the proposed method is feasible and effective for FE model updating on plate girder bridges.

• Journal of Korean Association for Spatial Structures
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• 제1권1호
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• pp.143-155
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• 2001

Generally, truss design has been determined by the designer's experience and intuition. But if we perform the most economical structural design we must consider not only cross-sections of members but also configurations(howe, warren and pratt types etc.) of single truss as the number of panel and truss height. The purpose of this study is to develope automated optimum design techniques for steel truss structures considering cross-sections of members and shape of trusses simultaneously. As the results, it could be possible to find easily the optimum solutions subject to design conditions at the preliminary structural design stage of the steel truss structures. In this study, the objective function is expressed as the whole member weight of trusses, and the applied constraints are as stresses, slenderness ratio, local buckling, deflection, member cross-sectional dimensions and truss height etc. The automated optimum design algorithm of this study is divided into three-level procedures. The first level on member cross-sectional optimization is performed by the sequential unconstrained minimization technique(SUMT) using dynamic programming method. And the second level about truss height optimization is applied for obtaining the optimum truss height by three-equal interval search method. The last level of optimization is applied for obtaining the optimum panel number of truss by integer programming method. The algorithm of multi-level optimization programming technique proposed in this study is more helpful for the economical design of plane trusses as well as space trusses.

• Advances in concrete construction
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• 제14권3호
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• pp.185-194
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• 2022

For producing cement and concrete, the construction field has been encouraged by the usage of industrial soil waste (or) secondary materials since it decreases the utilization of natural resources. Simultaneously, for ensuring the quality, the analyses of the strength along with durability properties of that sort of cement and concrete are required. The prediction of strength along with other properties of High-Performance Concrete (HPC) by optimization and machine learning algorithms are focused by already available research methods. However, an error and accuracy issue are possessed. Therefore, the Enhanced Deep Neural Network (EDNN) based strength along with durability prediction of HPC was utilized by this research method. Initially, the data is gathered in the proposed work. Then, the data's pre-processing is done by the elimination of missing data along with normalization. Next, from the pre-processed data, the features are extracted. Hence, the data input to the EDNN algorithm which predicts the strength along with durability properties of the specific mixing input designs. Using the Switched Multi-Objective Jellyfish Optimization (SMOJO) algorithm, the weight value is initialized in the EDNN. The Gaussian radial function is utilized as the activation function. The proposed EDNN's performance is examined with the already available algorithms in the experimental analysis. Based on the RMSE, MAE, MAPE, and R² metrics, the performance of the proposed EDNN is compared to the existing DNN, CNN, ANN, and SVM methods. Further, according to the metrices, the proposed EDNN performs better. Moreover, the effectiveness of proposed EDNN is examined based on the accuracy, precision, recall, and F-Measure metrics. With the already-existing algorithms i.e., JO, GWO, PSO, and GA, the fitness for the proposed SMOJO algorithm is also examined. The proposed SMOJO algorithm achieves a higher fitness value than the already available algorithm.

• Journal of the Korean Society for Precision Engineering
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• 제19권5호
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• pp.29-35
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• 2002

This study shows the process design and forming analysis of permalloy shielding can that support the automobile multi-display parts to indicate the accurate information of car. This study is particularly important, since the accuracy of permalloy shielding can is known to affect the magnetic properties such as coercivity and permeability quite sensitively. The objective functions are defects such as hemming wind, hemming length, hemming wrap and tightness in prehemming process. The pre-hemming angle is considered as design parameter. The commercial finite element program PAM-STAMP™ was used to simulate the pre-hemming and hemming process. The ANN (Artificial Neural Network) has been implemented for minimizing of objective function and for investigating effect of punch angle relevant to the pre-hemming process. The results of analysis to validate the proposed design method are presented.

• Proceedings of the KIEE Conference
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• 대한전기학회 2002년도 하계학술대회 논문집 A
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• pp.127-129
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• 2002

This paper presents a fuzzy-GA method to resolve dispersed generator placement for distribution systems. The problem formulation considers an objective to reduce power loss costs of distribution systems and the constraints with the number or size of dispersed generators and the deviation of the bus voltage. The main idea of solving fuzzy nonlinear goal programming is to transform the original objective function and constraints into the equivalent multi-objectives functions with fuzzy sets to evaluate their imprecise nature and solve the problem using the proposed genetic algorithm, without any transformation for this nonlinear problem to a linear model or other methods. The method proposed is applied to the sample systems to demonstrate its effectiveness.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• 제15권2호
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• pp.225-231
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• 2005

This paper presents a design method for the structural-acoustic coupled radiator that can emit sound in the desired direction. A coupled system that has a finite space and a semi-infinite space separated by two flexible walls and an opening is considered. An objective function is selected to maximize radiation power on a main axis and minimize a side lobe level. To get initial values, prediction of a pressure distribution on field points and radiation pattern of the structural-acoustic coupling system is shown at a coupled-resonant frequency. Three different optimization methods are adapted to design the coupled radiator. Pressure and intensity distribution of the designed radiator is presented.

• Smart Structures and Systems
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• 제15권5호
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• pp.1253-1270
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• 2015

In this paper Magnetic Charged System Search (MCSS) and Particle Swarm Optimization (PSO) are applied to the problem of damage detection using frequencies and mode shapes of the structures. The objective is to identify the location and extent of multi-damage in structures. Both natural frequencies and mode shapes are used to form the required objective function. To moderate the effect of noise on measured data, a penalty approach is applied. A variety of numerical examples including two beams and two trusses are considered. A comparison between the PSO and MCSS is conducted to show the efficiency of the MCSS in finding the global optimum. The results show that the present methodology can reliably identify damage scenarios using noisy measurements and incomplete data.