• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.6
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• pp.864-870
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• 2003

In recent engineering, the designer has become more and more dependent on the computer simulations such as FEM(Finite Element Method) and BEM(Boundary Element Method). In order to optimize such implicit models more efficiently and reliably, the meta -modeling technique has been developed for solving such a complex problems combined with the DACE(Design and Analysis of Computer Experiments). It is widely used for exploring the engineer's design space and for building approximation models in order to facilitate an effective solution of multi-objective and multi-disciplinary optimization problems. Optimization of a train suspension is performed according to the minimization of forty -six responses that represent ten ride comforts, twelve derailment quotients, twelve unloading ratios, and twelve stabilities by using the Kriging model of a train suspension. After each Kriging model is constructed, multi -objective optimal solutions are achieved by using a nonlinear programming method called SQP(Sequential Quadratic Programming).

• Journal of Korean Society on Water Environment
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• v.34 no.6
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• pp.591-601
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• 2018

Optimized BMP plans for controlling water quality using the Pareto trade-off surface curve in upper basin of Namgang Dam is proposed. The proposed alternatives consist of BMP installation scenarios in which the reduction efficiency of non-point pollutants is maximized in a given budget. The multi-objective optimization process for determining the optimal alternatives was performed without direct implementation of a watershed model such as SWAT analysis, thereby reducing the time taken. The shortening of the calculation time further enhances the applicability of the multi-objective optimization technique in preparing regional water quality management alternatives. In this study, different types of BMP are applied depending on the land use conditions. Fertilizer input control and vegetative filter strip are considered as alternatives to applying BMP to the field but only control of fertilizer input can be applied to rice paddies. Fertilizer input control and vegetative filter strip can be installed separately or simultaneously in a hydrologic response unit. Finally, 175 BMP application alternatives were developed for the water quality management of the upper river basin of Namgang dam. The proposed application alternative can be displayed on the map, which has the advantage of clearly defining the BMP installation location.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.423-432
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• 2014

Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is applied for solving Combined Economic Emission Dispatch (CEED) problem with valve-point loading of thermal generators. This CEED problem with valve-point loading is a nonlinear, constrained multi-objective optimization problem, with power balance and generator capacity constraints. The valve-point loading introduce ripples in the input-output characteristics of generating units and make the CEED problem as a nonsmooth optimization problem. To validate its effectiveness of NSGA-II, two benchmark test systems, IEEE 30-bus and IEEE 118-bus systems are considered. To compare the Pareto-front obtained using NSGA-II, reference Pareto-front is generated using multiple runs of Real Coded Genetic Algorithm (RCGA) with weighted sum of objectives. Comparison with other optimization techniques showed the superiority of the NSGA-II approach and confirmed its potential for solving the CEED problem. Numerical results show that NSGA-II algorithm can provide Pareto-front in a single run with good diversity and convergence. An approach based on Technique for Ordering Preferences by Similarity to Ideal Solution (TOPSIS) is applied on non-dominated solutions obtained to determine Best Compromise Solution (BCS).

• Structural Engineering and Mechanics
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• v.43 no.6
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• pp.795-821
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• 2012

The size and topology of geometrically nonlinear dome structures are optimized thereby minimizing both its entire weight & joint (node) displacements and maximizing load-carrying capacity. Design constraints are implemented from provisions of American Petroleum Institute specification (API RP2A-LRFD). In accordance with the proposed design constraints, the member responses computed by use of arc-length technique as a nonlinear structural analysis method are checked at each load increment. Thus, a penalization process utilized for inclusion of unfeasible designations to genetic search is correspondingly neglected. In order to solve this complex design optimization problem with multiple objective functions, Non-dominated Sorting Genetic Algorithm II (NSGA II) approach is employed as a multi-objective optimization tool. Furthermore, the flexibility of proposed optimization is enhanced thereby integrating an automatic dome generating tool. Thus, it is possible to generate three distinct sphere-shaped dome configurations with varying topologies. It is demonstrated that the inclusion of brace (diagonal) members into the geometrical configuration of dome structure provides a weight-saving dome designation with higher load-carrying capacity. The proposed optimization approach is recommended for the design optimization of geometrically nonlinear dome structures.

• Journal of the Society of Naval Architects of Korea
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• v.42 no.2 s.140
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• pp.175-182
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• 2005

It is necessary to develop an efficient optimization technique to optimize the engineering structures which have given design spaces, discrete design values and several design goals. As optimization techniques, direct search method and stochastic search method are widely used in designing of engineering structures. The merit of the direct search method is to search the optimum points rapidly by considering the search direction, step size and convergence limit. And the merit of the stochastic search method is to obtain the global optimum points by spreading point randomly entire the design spaces. In this paper, a Pareto optimal based multi-objective function method (PMOFM) is developed by considering the search direction based on Pareto optimal points, step size, convergence limit and random search generation . The PMOFM can also apply to the single objective function problems, and can consider the discrete design variables such as discrete plate thickness and discrete stiffener spaces. The design results are compared with existing Evolutionary Strategies (ES) method by performing the design of double bottom structures which have discrete plate thickness and discrete stiffener spaces.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2A
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• pp.223-231
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• 2008

This research presents a new maintenance planning method for deteriorating bridges considering simultaneously the minimization of the maintenance cost and maximization of the bridge performance. Optimal maintenance planning is formulated as a multi-objective optimization problem that treats the maintenance cost as well as the bridge performance such as the condition grade of the bridge deck, girder and pier. To effectively address the multi-objective optimization problem and decision making process for the obtained solution set, we apply a genetic algorithm as a numerical searching technique and adopt a preference-based optimization method. A numerical example for a typical 5-span prestressed concrete girder bridge shows that the maintenance cost and the performance of the bridge can be balanced reasonably without severe trade-offs between each objectives.

• Journal of the Society of Naval Architects of Korea
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• v.49 no.1
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• pp.68-78
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• 2012

A layout of an LNG FPSO should be elaborately determined as compared with that of an onshore plant because many topside process systems are installed on the limited area; the deck of the LNG FPSO. Especially, the layout should be made as multi-deck, not single-deck and have a minimum area. In this study, a multi-floor layout for the liquefaction process, the dual mixed refrigerant(DMR) cycle, of LNG FPSO was determined by using the optimization technique. For this, an optimization problem for the multi-floor layout was mathematically formulated. The problem consists of 589 design variables representing the positions of topside process systems, 125 equality constraints and 2,315 inequality constraints representing limitations on the layout of them, and an objective function representing the total layout cost. To solve the problem, a hybrid optimization method that consists of the genetic algorithm(GA) and sequential quadratic programming(SQP) was used in this study. As a result, we can obtain a multi-floor layout for the liquefaction process of the LNG FPSO which satisfies all constraints related to limitations on the layout.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.4
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• pp.591-598
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• 2002

In the ship structural design, the material cost of hull weight and the overall cost of construction processes should be minimized considering safety and reliability. In the past, minimum weight design has been mainly focused on reducing material cost and increasing dead weight reflect the interests of a ship's owner. But, in the past experience, the minimum weight design has been inevitably lead to increasing the construction cost. Therefore, it is necessary that the designer of ship structure should consider both structural weight and construction cost. In this point of view, multi-objective optimization technique is proposed to design the ship structure in this study. According to the proposed algorithm, the results of optimization were compared to the structural design of actual VLCC(Very Large Crude Oil Carrier). Objective functions were weight cost and construction cost of VLCC, and ES(Evolution Strategies), one of the stochastic search methods, was used as an optimization solver. For the scantlings of members and the estimations of objectives, classification rule was adopted for the longitudinal members, and the direct calculation method, GSDM(Generalized Slope Deflection Method), lot the transverse members. To choose the most economical design point among the results of Pareto optimal set, RFR(Required Freight Rate) was evaluated for each Pareto point, and compared to actual ship.

• Proceedings of the KSME Conference
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• 2001.11a
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• pp.378-383
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• 2001

In order to improve automobile maneuverability and tire durability, it is very important for one to determine a suitable sidewall contour producing the ideal tension and strain-energy distributions. In order to determine such a sidewall contour, one must apply multi-objective optimization technique. The optimization problem of tire carcass contour involves several objective functions. Hence, we execute the tire contour optimization for improving the maneuverability and the tire durability using satisficing trade-off method. And, the tire optimization also requires long cup time for the sensitivity analysis. In order to resolve this numerical difficulty, we apply neural network algorithm.

• Journal of the Korean Geotechnical Society
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• v.18 no.1
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• pp.71-78
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• 2002

This paper presents a back-calculation technique leer the prediction of the behavior of earth wall inserted in multi-layered soil deposit. The soil properties are back-calculated from the measured displacement at each construction stage and the behavior of earth wall far the next construction stage is predicted using back-calculated soil properties. For multi-layered soil deposit, the back-calculation would be very difficult due to the increase in the number of variables. In this study, to solve this difficulty, the back-calculation was performed successively from the lowest layer to the upper layers. An efficient elasto-plastic beam-column analysis was used for forward analysis to minimize the computation time of iterative back-calculation procedure. The coefficients of subgrade reaction and lateral earth pressure necessary for the formation of p-y curve were selected as back calculation variables, and to minimize the effect of abnormal behavior of the wall which might be caused by any unexpected action during construction, the difference between measured displacement increment and computed displacement increment at each construction stages is used as the objective function of optimization. The constrained sequential linear programming was used for the optimization technique to found values of variables minimizing the objective function. The proposed method in this study was verified using numerically generated data and measured field data.