• Structural Engineering and Mechanics
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• v.6 no.8
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• pp.857-870
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• 1998

This paper deals with a special class of inverse problems in discrete structural plasticity involving the identification of elastic limits and hardening moduli on the basis of information on displacements. The governing equations lead naturally to a special and challenging optimization problem known as a Mathematical Program with Equilibrium Constraints (MPEC), a key feature of which is the orthogonality of two sign-constrained vectors or so-called "complementarity" condition. We investigate numerically the application of two simple algorithms, both based on the use of the general purpose nonlinear programming code CONOPT accessed via the GAMS modeling language, for solving the suitably reformulated problem. Application is illustrated by means of two numerical examples.

• Journal of Mechanical Science and Technology
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• v.15 no.8
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• pp.1119-1131
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• 2001

In this paper we formulate an optimization based approach to determining the maximally inscribed rectangle in a robots workspace. The size and location of the maximally inscribed rectangle is an effective index for evaluating the size and quality of a robots workspace. Such information is useful for, e. g., optimal worktable placement, and the placement of cooperating robots. For general robot workspaces we show how the problem can be formulated as a constrained nonlinear optimization problem possessing a special structure, to which standard numerical algorithms can be applied. Key to the rapid convergence of these algorithms is the choice of a starting point; in this paper we develop an efficient computational geometric algorithm for rapidly obtaining an approximate solution suitable as an initial starting point. We also develop an improved version of the algorithm of Haug et al. for calculating a robots workspace boundary.

• 전기의세계
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• v.24 no.5
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• pp.72-80
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• 1975

In this paper an application of the Monte Carlo method to optimum circuit design is discussed. T. Tsuda and T. Kiyono's algorithm based on the Monte Carlo method for solving multiple simul-taneous nonlinear equations is generalized to apply it to finding solutions of the constrained nonlinear optimization problem. The generalized algorithm derived here is directly applied to economical circuit design. In the cirsuit design, the object function is a cost function which is related to the cost of each circuit component. The constraint is the variance of the total system expressed by the variances of each circuit component. The design is to be determined so that the circuit has specified drift reliability with minimum cost. A practical example of economical circuit design and a general nonlinear function minimization is presented with food results.

• Advances in Energy Research
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• v.4 no.4
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• pp.255-274
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• 2016

This paper presents a novel symbiotic organisms search (SOS) algorithm to optimize both real power loss (RPL) and voltage stability limit (VSL) of a transmission network by controlling the variables such as unified power flow controller (UPFC) location, UPFC series injected voltage magnitude and phase angle and transformer taps simultaneously. Mathematically, this issue can be formulated as nonlinear equality and inequality constrained multi objective, multi variable optimization problem with a fitness function integrating both RPL and VSL. The symbiotic organisms search (SOS) algorithm is a nature inspired optimization method based on the biological interactions between the organisms in ecosystem. The advantage of SOS algorithm is that it requires a few control parameters compared to other meta-heuristic algorithms. The proposed SOS algorithm is applied for solving optimum control variables for both single objective and multi-objective optimization problems and tested on New England 39 bus test system. In the single objective optimization problem only RPL minimization is considered. The simulation results of the proposed algorithm have been compared with the results of the algorithms like interior point successive linear programming (IPSLP) and bacteria foraging algorithm (BFA) reported in the literature. The comparison results confirm the efficacy and superiority of the proposed method in optimizing both single and multi objective problems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.8
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• pp.917-920
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• 2016

SpSF algorithm is direction-of-arrival estimation algorithm based on sparse representation of incident signlas. Cost function to be optimized for DOA estimation is multi-dimensional nonlinear function, which is hard to handle for optimization. After some manipulation, the problem can be cast into convex optimiztion problem. Convex optimization problem tuns out to be constrained optimization problem, where the parameter in the constraint has to be determined. The solution of the convex optimization problem is dependent on the specific parameter value in the constraint. In this paper, we propose a rule-of-thumb for determining the parameter value in the constraint. Based on the fact that the noise in the array elements is complex Gaussian distributed with zero mean, the average of the Frobenius norm of the matrix in the constraint can be rigorously derived. The parameter in the constrint is set to be two times the average of the Frobenius norm of the matrix in the constraint. It is shown that the SpSF algorithm actually works with the parameter value set by the method proposed in this paper.

• Journal of Mechanical Science and Technology
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• v.18 no.9
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• pp.1590-1603
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• 2004

In this study the optimization of plate-fin type heat sink with vortex generator for the thermal stability is performed numerically. The optimum solutions in the heat sink are obtained when the temperature rise and the pressure drop are minimized simultaneously. Thermal performance of heat sink is influenced by the heat sink shape such as the base-part fin width, lower-part fin width, and basement thickness. To acquire the optimal design variables automatically, CFD and mathematical optimization are integrated. The flow and thermal fields are predicted using the finite volume method. The optimization is carried out by means of the sequential quadratic programming (SQP) method which is widely used for the constrained nonlinear optimization problem. The results show that the optimal design variables are as follows; B$_1$=2.584 mm, B$_2$=1.741 mm, and t=7.914 mm when the temperature rise is less than 40 K. Comparing with the initial design, the temperature rise is reduced by 4.2 K, while the pressure drop is increased by 9.43 Pa. The relationship between the pressure drop and the temperature rise is also presented to select the heat sink shape for the designers.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.5
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• pp.56-64
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• 2006

Station collocation of closely placed multiple GEO spacecraft is required to avoid the problem of collision risk, attitude sensor interference and/or occultation. This paper presents the method of obtaining the orbit correction scheme for collocating two GEO spacecraft within a small station-keeping box. The relative motion of each spacecraft with respect to the virtual geostationary satellite is precisely expressed in terms of power and trigonometry functions. This closed-form orbit propagator is used to define the constraint conditions which meet the requirements for the station collocation. Finally, the technique of constrained optimization is used to find the orbit maneuver sequence. Nonlinear simulations are performed and their results are compared with those of the classical method.

• Proceedings of the KIEE Conference
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• 2001.07b
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• pp.904-906
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• 2001

This paper presents a magnetic circuit design procedure by using Response Surface Methodology(RSM) to determine initial and detail design parameters for reducing torque ripple in BLDC motor of Electric Power Steering (EPS). RSM is achieved through using the experiment design method in combination with Finite Element Method and well adapted to make analytical model for a complex problem considering a lot of interaction of design variable Moreover, Sequential Quadratic Problem (SQP) method is used to solve the relsulting of constrained nonlinear optimization problem.

• Journal of the Korean Geotechnical Society
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• v.24 no.3
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• pp.5-11
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• 2008

This paper pertains to the incorporation of a genetic algorithm methodology for determining the critical slip surface and the corresponding factor of safety of soil slopes using inclined slice method. The analysis is formulated as a constrained optimization problem to solve the nonlinear equilibrium equations and finding the factor of safety and the critical slip surface. The sensitivity of GA optimization method is presented in terms of development of failure surface. Example problem is presented to demonstrate the efficiencies of the genetic algorithm approach. The results obtained by this method are compared with other traditional optimization technique.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.3
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• pp.31-38
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• 2003

In the present work, a nonlinear inverse perturbation method which has been used in the structural optimization, is adopted so as to identify the structural damages. Unlike the structural optimization, a larger number of constrained equations than the number of unknown parameters are often required detect structural damage. Therefore, nonlinear least squares method is utilized to solve the problem. Because only a limited number of sensors are available I real situation of damage detection, the determination of sensor location becomes one of the most important issues. Hence, this work concentrates on the issue of sensor placement in the framework of nonlinear inverse perturbation method, and the performances of various methodologies concerning to sensor placement are compared with each other. The comparisons show tat the successive elimination method gets good performance for sensor placement. From the several numerical studies, it is confirmed that the inverse perturbation method, combined with the successive elimination method, is very promising in structural damage detection.