• Journal of the Korea Society for Simulation
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• v.3 no.2
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• pp.57-67
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• 1994

For many practical and industrial optimization problems where some or all of the system components are stochastic, the objective functions cannot be represented analytically. Therefore, modeling by computer simulation is one of the most effective means of studying such complex systems. In this paper, with discussion of simulation optimization techniques, a case study in machining process for application of simulation optimization is presented. Most of optimization techniques can be classified as single-or multiple-response techniques. The optimization of single-response category, these strategies are gradient based search methods, stochastic approximate method, response surface method, and heuristic search methods. In the multiple-response category, there are basically five distinct strategies for treating the responses and finding the optimum solution. These strategies are graphical method, direct search method, constrained optimization, unconstrained optimization, and goal programming methods. The choice of the procedure to employ in simulation optimization depends on the analyst and the problem to be solved.

• Management Science and Financial Engineering
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• v.13 no.1
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• pp.1-24
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• 2007

I propose new combined randomized methods for global optimization problems. These methods are based on the Nested Partitions(NP) method, a useful method for simulation optimization which guarantees global optimal solution but has several shortcomings. To overcome these shortcomings I hired various statistical selection methods and combined with NP method. I first explain the NP method and statistical selection method. And after that I present a detail description of proposed new combined methods and show the results of an application. As well as, I show how these combined methods can be considered in case of computing budget limit problem.

• Nonlinear Functional Analysis and Applications
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• v.27 no.4
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• pp.869-879
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• 2022

In this paper, we consider matrix optimization problems. We investigate augmented Lagrangian methods of multipliers and alternating direction methods of multipliers for the problems. Following the proofs of Eckstein [3], and Eckstein and Yao [5], we prove convergence theorems for augmented Lagrangian methods of multipliers and alternating direction methods of multipliers for the problems.

• Structural Engineering and Mechanics
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• v.46 no.3
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• pp.403-416
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• 2013

This paper describes new optimization strategy that offers significant improvements in performance over existing methods for geometry design of frame structures. In this study, an imperialist competitive algorithm (ICA) and ant colony optimization (ACO) are combined to reach to an efficient algorithm, called Imperialist Competitive Ant Colony Optimization (ICACO). The ICACO applies the ICA for global optimization and the ACO for local search. The results of optimal geometry for three benchmark examples of frame structures, demonstrate the effectiveness and robustness of the new method presented in this work. The results indicate that the new technique has a powerful search strategies due to the modifications made in search module of ICACO. Higher rate of convergence is the superiority of the presented algorithm in comparison with the conventional mathematical methods and non hybrid heuristic methods such as ICA and particle swarm optimization (PSO).

• Proceeding of KASS Symposium
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• 2005.05a
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• pp.3-51
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• 2005

Optimization methods are presented for design of shells and spatial structures. The effectiveness of using optimization techniques are demonstrated by the following examples: 1. Shape design of ribbed shells. 2. Shape design of membrane structures. 3. Optimization of single-layer spatial truss against buckling. 4. Application of heuristic methods to optimization of space frames. The readers may first see the numerical results to find that is possible by optimization. In the appendix, overview of structural optimization in architectural design is presented, and effectiveness of optimization is demonstrated by small examples. Each chapter is a part of a published paper, or translation from a Japanese article. So there might be some difficulties for understanding the details: inconsistency of the story, etc., which the author hope not to lead to major difficulties for understanding the concepts and results.

• Journal of the Society of Naval Architects of Korea
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• v.46 no.4
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• pp.409-416
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• 2009

The structural design problems are acknowledged to be commonly multi-criteria in nature. The various multi-criteria optimization methods are reviewed and the most efficient and easy-to-use Pareto optimal solution methods are applied to structural optimization of a truss and a beam. The result of the study shows that Pareto optimal solution methods can easily be applied to structural optimization with multiple objectives, and the designer can have a choice from those Pareto optimal solutions to meet an appropriate design environment.

• Structural Engineering and Mechanics
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• v.55 no.6
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• pp.1121-1137
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• 2015

High powered computers and engineering computer systems allow designers to routinely simulate complex physical phenomena. The presented work deals with the analysis of two finite element method optimization techniques (First Order Method-FOM and Subproblem Approximation Method-SAM) implemented in the individual Design Optimization module in the Ansys software to analyze the behavior of real problems. A design optimization is a difficult mathematical process, intended to find the minimum or maximum of an objective function, which is mostly based on iterative procedure. Using optimization techniques in engineering designs requires detailed knowledge of the analyzed problem but also an ability to select the appropriate optimization method. The methods embedded in advanced computer software are based on different optimization techniques and their efficiency is significantly influenced by the specific character of a problem. The efficiency, robustness and accuracy of the methods are studied through strictly convex two-dimensional optimization problem, which is represented by volume minimization of two bars' plane frame structure subjected to maximal vertical displacement limit. Advantages and disadvantages of the methods are described and some practical tips provided which could be beneficial in any efficient engineering design by using an optimization method.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.5
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• pp.112-118
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• 2000

In case ESO(evolutionary structural optimization) which is one of topology optimization methods, the element removal ratio is fixed throughout topology optimization by 1 or 2%. As a result it has no flexibility for various types of structures and thus the rate of convergence might not be efficient. Thus various element removal methods were developed in order to improve the efficiency of ESO. In this paper, various element removal methods for ESO are compared with each other for a bracket and a short cantilever. In addition, a new improved bi-directional element removal method is suggested in order to obtain much better optimized topology. From the comparative results of the examples, it is verified that all of the developed various element removal methods are very effective, and the suggested element removal method is the most effective.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.130-135
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• 2008

An aerodynamic optimization design process of multistage axial turbine is presented in this article: first, applying quasi-three dimensional(Q3D) design methods to conduct preliminary design and then adopting modern optimization design methods to implement multistage local optimization. Quasi-three dimensional(Q3D) design methods, which mainly refer to S2 flow surface direct problem calculation, adopt the S2 flow surface direct problem calculation program of Harbin Institute of Technology. Multistage local optimization adopts the software of Numeca/Design3D, which jointly adopts genetic algorithm and artificial neural network. The major principle of the methodology is that the successive design evaluation is performed by using an artificial neural network instead of a flow solver and the genetic algorithms may be used in an efficient way. Flow computation applies three-dimensional viscosity Navier Stokes(N-S) equation solver. Such optimization process has three features: (i) local optimization based on aerodynamic performance of every cascade; (ii) several times of optimizations being performed to every cascade; and (iii) alternate use of coarse grid and fine grid. Such process was applied to optimize a three-stage axial turbine. During the optimization, blade shape and meridional channel were respectively optimized. Through optimization, the total efficiency increased 1.3% and total power increased 2.4% while total flow rate only slightly changed. Therefore, the total performance was improved and the design objective was achieved. The preliminary design makes use of quasi-three dimensional(Q3D) design methods to achieve most reasonable parameter distribution so as to preliminarily enhance total performance. Then total performance will be further improved by adopting multistage local optimization design. Thus the design objective will be successfully achieved without huge expenditure of manpower and calculation time. Therefore, such optimization design process may be efficiently applied to the aerodynamic design optimization of multistage axial turbine.

• Journal of the Ergonomics Society of Korea
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• v.31 no.6
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• pp.733-740
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• 2012

Objective: The present study systematically analyzed the characteristics of ergonomic layout optimization methods by a comprehensive literature survey. Background: Although layout design methods for ergonomic placement of controls and displays on a console have been developed, understanding of their characteristics is lacking. Method: The present study analyzed layout optimization papers published past 20 years from the following four aspects: optimization model, optimization algorithm, design principle, and constraint/assumption. Results: The existing layout optimization methods based on various optimization techniques consider only a partial set of four layout principles(importance, frequency of use, sequence of use, and functional grouping) and two ergonomic criteria(visibility and reach). In addition, the existing methods oversimplify components in various sizes, shapes, and angles by assuming the equality of the components in size and shape. Conclusion: A more effective layout optimization method is needed which considers the layout principles and ergonomic criteria in a comprehensive manner and reflect the diversity of components in size and shape. Application: The identified characteristics on the existing layout optimization methods can be applicable to development of a better ergonomic console layout design method.