• Structural Engineering and Mechanics
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• v.81 no.6
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• pp.677-689
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• 2022

Generally, the goal of seismic retrofit design of an existing structure using energy dissipation devices is to determine the optimum design parameters of a retrofit device to satisfy a specified limit state with minimum cost. However, the presence of multiple parameters to be optimized and the computational complexity of performing non-linear analysis make it difficult to find the optimal design parameters in the realistic 3D structure. In this study, genetic algorithm-based optimal seismic retrofit methods for determining the required number, yield strength, and location of steel slit dampers are proposed to retrofit an asymmetric soft first-story structure. These methods use a multi-objective and single-objective evolutionary algorithms, each of which varies in computational complexity and incorporates nonlinear time-history analysis to determine seismic performance. Pareto-optimal solutions of the multi-objective optimization are found using a non-dominated sorting genetic algorithm (NSGA-II). It is demonstrated that the developed multi-objective optimization methods can determine the optimum number, yield strength, and location of dampers that satisfy the given limit state of a three-dimensional asymmetric soft first-story structure. It is also shown that the single-objective distribution method based on minimizing plan-wise stiffness eccentricity turns out to produce similar number of dampers in optimum locations without time consuming nonlinear dynamic analysis.

• Structural Engineering and Mechanics
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• v.26 no.4
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• pp.459-477
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• 2007

A bi-directional tuned mass damper (BTMD) in which a mass connected by two translational springs and two viscous dampers in two orthogonal directions has been introduced to control coupled lateral and torsional vibrations of asymmetric building. An efficient control strategy has been presented in this context to control displacements as well as acceleration responses of asymmetric buildings having asymmetry in both plan and elevation. The building is idealized as a simplified 3D model with two translational and a rotational degrees of freedom for each floor. The principles of rigid body transformation have been incorporated to account for eccentricity between center of mass and center of rigidity. The effective and robust design of BTMD for controlling the vibrations in structures has been presented. The redundancy of optimum design has been checked. Non dominated sorting genetic algorithm (NSGA) has been used for tuning optimum stages and locations of BTMDs and its parameters for control of vibration of seismically excited buildings. The optimal locations have been observed to be reasonably compact and practically implementable.

• 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.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.4
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• pp.439-449
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• 2018

In this paper, multi-objective optimization of a multi-bubble pressure cabin in the underwater glider with Blended-Wing-Body (BWB) is carried out using Kriging and the Non-dominated Sorting Genetic Algorithm (NSGA-II). Two objective functions are considered: buoyancy-weight ratio and internal volume. Multi-bubble pressure cabin has a strong compressive capacity, and makes full use of the fuselage space. Parametric modeling of the multi-bubble pressure cabin structure is automatic generated using UG secondary development. Finite Element Analysis (FEA) is employed to study the structural performance using the commercial software ANSYS. The weight of the primary structure is determined from the volume of the Finite Element Structure (FES). The stress limit is taken into account as the constraint condition. Finally, Technique for Ordering Preferences by Similarity to Ideal Solution (TOPSIS) method is used to find some trade-off optimum design points from all non-dominated optimum design points represented by the Pareto fronts. The best solution is compared with the initial design results to prove the efficiency and applicability of this optimization method.

• Journal of Environmental Impact Assessment
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• v.22 no.6
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• pp.713-724
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• 2013

In terms of waste load allocation, inequality of waste load discharge must be considered as well as economic aspects such as minimization of waste load abatement. The inequality of waste load discharge between areas was calculated with Gini coefficient and was included as one of the objective functions of the multi-objective waste load allocation. In the past, multi-objective functions were usually weighted and then transformed into a single objective optimization problem. Recently, however, due to the difficulties of applying weighting factors, multi-objective genetic algorithms (GA) that require only one execution for optimization is being developed. This study analyzes multi-objective waste load allocation using NSGA-II-aJG that applies Pareto-dominance theory and it's adaptation of jumping gene. A sensitivity analysis was conducted for the parameters that have significant influence on the solution of multi-objective GA such as population size, crossover probability, mutation probability, length of chromosome, jumping gene probability. Among the five aforementioned parameters, mutation probability turned out to be the most sensitive parameter towards the objective function of minimization of waste load abatement. Spacing and maximum spread are indexes that show the distribution and range of optimum solution, and these two values were the optimum or near optimal values for the selected parameter values to minimize waste load abatement.

• Smart Structures and Systems
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• v.16 no.1
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• pp.1-26
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• 2015

Minimizing construction cost and reducing seismic damage are two conflicting objectives in the design of any new structure. In the present work, we try to develop a framework in order to solve the optimum performance-based design problem considering the construction cost and the seismic damage of steel moment-frame structures. The Park-Ang damage index is selected as the seismic damage measure because it is one of the most realistic measures of structural damage. The non-dominated sorting genetic algorithm (NSGA-II) is employed as the optimization algorithm to search the Pareto optimal solutions. To improve the time efficiency of the proposed framework, three simplifying strategies are adopted: first, simplified nonlinear modeling investigating minimum level of structural modeling sophistication; second, fitness approximation decreasing the number of fitness function evaluations; third, wavelet decomposition of earthquake record decreasing the number of acceleration points involved in time-history loading. The constraints of the optimization problem are considered in accordance with Federal Emergency Management Agency's (FEMA) recommended seismic design specifications. The results from numerical application of the proposed framework demonstrate the efficiency of the framework in solving the present multi-objective optimization problem.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.3 s.234
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• pp.455-461
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• 2005

This research studied robust design of composite hand for LTR (LCD glass Transfer Robot). $1^{st}$ DOE (Design of Experiment) was conducted to find out vital few Xs. 108 experiments were performed and their results were statistically analyzed. Pareto chart analysis shows that the geometric parameters (height and width of composite beam) are more important than material parameters $(E_{1},\;E_{2})$ or stacking sequence angle. Also, the stacking sequence of mid-layer is more important than that of outer-layer. The main effect plots shows that the maximum deflection of LTR hand is minimized with increasing height, width of beam and layer thickness. $2^{nd}$ DOE was conducted to obtain RSM (Response Surface Method) equation. 25 experiments were conducted. The CCD (Central Composite Design) technique with four factors was used. The coefficient of determination $(R^{2})$ for the calculated RSM equation was 0.989. Optimum design was conducted using the RSM equation. Multi-island genetic algorithm was used to optimum design. Optimum values for beam height, beam width, layer thickness and beam length were 24.9mm, 186.6mnL 0.15mm and 2402.4mm respectively. An approximate value of 0.77mm in deflection was expected to be a maximum under the optimum conditions. Six sigma robust design was conducted to find out guideline for control range of design parameter. To acquire six sigma level reliability, the standard deviation of design parameter should be con trolled within $2{\%}$ of average design value

• Journal of Intelligence and Information Systems
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• v.12 no.2
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• pp.99-123
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• 2006

In an effect to composite an optimal supply chain, this study has introduced an agent-based negotiation as a method to assign a lot of orders to a large number of participants. As a resources allocation mechanism to form a strategic cooperation based on information sharing between supply chain members(buyers, manufacturers, suppliers), this agent negotiation provides coordination functions allowing all participants to make a profit and accomplishing Pareto optimum solution from the viewpoint of a whole supply chain. A SET model-based scheduling takes into consideration both earliness production cost and tardiness production cost, along with a competitive relationship between multiple participants. This study has tried to prove that the result of an agent-based negotiation is a Pareto optimal solution under the dynamic supply chain environment, establishing the mathematical formulation for a performance test, and making a comparison with the heuristic Branch & Bound method.

• Journal of Electrical Engineering and Technology
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• v.11 no.1
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• pp.20-28
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• 2016

This paper presents a generation rescheduling method for the enhancement of transient stability in power systems. The priority and the candidate generators for rescheduling are calculated by using the energy margin sensitivity. The generation rescheduling formulates the Lagrangian function with the fuel cost and emission such as NO_x and SO_x from power plants. The generation rescheduling searches for the solution that minimizes the Lagrangian function by using the Newton’s approach. While the Pareto optimum in the fuel cost and emission minimization has a drawback of finding a number of non-dominated solutions, the proposed approach can explore the non-inferior solutions of the multiobjective optimization problem more efficiently. The method proposed is applied to a 4-machine 6-bus system to demonstrate its effectiveness.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.2
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• pp.88-95
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• 2008

With society focusing more and more on environmental issues, the recycling of materials of all types has become an important concern. In this paper, optimization method is developed for reducing cost and improving quality in mill scale recycling. An experimental investigation into the process parameter effects is presented to determine the optimum configuration of parameters for performance, quality and cost. Taguchi's optimization approach was used to obtain the optimal parameters. The significant parameters were identified and their effects on mill scale recycling were studied. As a results, a confirmation experiment with the optimal levels of process parameters was carried out in order to demonstrate the effectiveness of the Taguchi method.