• 제목/요약/키워드: optimization problems

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Structural Optimization for Non-Linear Behavior Using Equivalent Static Loads (II) - Structural Examples - (선형 등가정하중을 이용한 비선형 거동 구조물의 최적설계 (II) - 구조예제 -)

  • Park Ki-Jong;Park Gyung-Jin
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.8 s.239
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    • pp.1061-1069
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    • 2005
  • In part I of this papter Nonlinear Response Optimization using Equivalent Static Loads (NROESL) method/algorithm is developed to conduct optimization for nonlinear behavior structures. The method/algorithm is also verified to show its convergency and optimality. In this present paper, the NROESL algorithm is applied to several structural problems with geometric and/or material nonlinearity. Conventional optimization with sensitivity analysis using the finite difference method is also applied to the same examples. The results of the optimizations are compared. The proposed method is very efficient and derives good solutions.

Development of Shape Optimization System for General Structures (일반 구조물에 대한 형상 최적화 시스템의 개발)

  • 한석영
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2000.04a
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    • pp.304-309
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    • 2000
  • Growth-strain method was used for shape optimization of general structures. It was verified that the growth-strain method is very effective for shape optimization of solid structures in previous papers, but It could not provide reasonable optimized shape for structures with holes inside. The purpose of this study is to improve the growth-strain method for shape optimization of two- and three- dimensional structures. In order to improve, the problems occurred as the growth-strain method was applied to general structures were examined, and then the improved method was suggested. Finally, an automatic shape optimization system was built up by the improved growth-strain method with finite element method. The effectiveness and practicality of the developed shape optimization system was verified by some examples.

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Multi-Phase Optimization of Quill Type Machine Structures(1) (Static Compliance Analysis & Multi-Objective Function Optimization) (퀼형 공작기계구조물의 다단계 최적화(1) (정강성 해석 및 다목적함수 최적화))

  • Lee, Yeong-U;Seong, Hwal-Gyeong
    • Journal of the Korean Society for Precision Engineering
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    • v.18 no.11
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    • pp.155-160
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    • 2001
  • To achieve high precision cutting as well as production capability in the machine tool, it is needed to develop excellent rigidity statically, dynamically and thermally as well. In order to predict the qualitative behavior of a machine tool, simultaneous analysis of mechanics and heat transfer is required. Generally, machine tool designers have solved designing problems based on partial estimation of the specified rigidity. This study clears the inter-relationship between therm, and propose multi-phase optimization of machine tool structure using a genetic algorithm. The multi-phase solution method is consists of a series of mechanical design problem. At this first phase of static design problem, multi-objective optimization for the purpose of minimization of the total weight and static compliance minimization is solved using the Pareto Genetic Algorithm.

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Parallel 3-D Aerodynamic Shape Optimization on Unstructured Meshes

  • Lee, Sang-Wook;Kwon, Oh-Joon
    • International Journal of Aeronautical and Space Sciences
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    • v.4 no.1
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    • pp.45-52
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    • 2003
  • A three-dimensional aerodynamic shape optimization technique in inviscid compressible flows is developed by using a parallel continuous adjoint formulation on unstructured meshes. A new surface mesh modification method is proposed to overcome difficulties related to patch-level remeshing for unstructured meshes, and the effect of design sections on aerodynamic shape optimization is examined. Applications are made to three-dimensional wave drag minimization problems including an ONERA M6 wing and the EGLIN wing-pylon-store configuration. The results show that the present method is robust and highly efficient for the shape optimization of aerodynamic configurations, independent of the number of design variables used.

Surrogate-Based Improvement on Cuckoo Search for Global Constrained Optimization (근사 최적화를 활용한 뻐꾸기 탐색법의 성능 개선)

  • Lee, Se Jung
    • Korean Journal of Computational Design and Engineering
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    • v.19 no.3
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    • pp.245-252
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    • 2014
  • Engineering applications of global optimization techniques are recently abundant in the literature and it may be caused by both new methodologies arising and faster computers coming out. Many of the optimization techniques are based on natural or biological phenomena. This study put focus on enhancing the performace of Cuckoo Search (CS) among them since it has the least number of parameters to tune. The proposed enhancement can be achieved by applying surrogate-based optimization at every cycle of CS, which fortifies the exploitation capability of the original method. The enhanced algorithm has been applied several engineering design problems with constraints. The proposed method shows comparable or superior performance to the original method.

A B-spline based Branch & Bound Algorithm for Global Optimization (전역 최적화를 위한 B-스플라인 기반의 Branch & Bound알고리즘)

  • Park, Sang-Kun
    • Korean Journal of Computational Design and Engineering
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    • v.15 no.1
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    • pp.24-32
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    • 2010
  • This paper introduces a B-spline based branch & bound algorithm for global optimization. The branch & bound is a well-known algorithm paradigm for global optimization, of which key components are the subdivision scheme and the bound calculation scheme. For this, we consider the B-spline hypervolume to approximate an objective function defined in a design space. This model enables us to subdivide the design space, and to compute the upper & lower bound of each subspace where the bound calculation is based on the LHS sampling points. We also describe a search tree to represent the searching process for optimal solution, and explain iteration steps and some conditions necessary to carry out the algorithm. Finally, the performance of the proposed algorithm is examined on some test problems which would cover most difficulties faced in global optimization area. It shows that the proposed algorithm is complete algorithm not using heuristics, provides an approximate global solution within prescribed tolerances, and has the good possibility for large scale NP-hard optimization.

Design of multi-span steel box girder using lion pride optimization algorithm

  • Kaveh, A.;Mahjoubi, S.
    • Smart Structures and Systems
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    • v.20 no.5
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    • pp.607-618
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    • 2017
  • In this research, a newly developed nature-inspired optimization method, the Lion Pride Optimization algorithm (LPOA), is utilized for optimal design of composite steel box girder bridges. A composite box girder bridge is one of the common types of bridges used for medium spans due to their economic, aesthetic, and structural benefits. The aim of the present optimization procedure is to provide a feasible set of design variables in order to minimize the weight of the steel trapezoidal box girders. The solution space is delimited by different types of design constraints specified by the American Association of State Highway and Transportation Officials. Additionally, the optimal solution obtained by LPOA is compared to the results of other well-established meta-heuristic algorithms, namely Gray Wolf Optimization (GWO), Ant Lion Optimizer (ALO) and the results of former researches. By this comparison the capability of the LPOA in optimal design of composite steel box girder bridges is demonstrated.

Shape and size optimization of trusses with dynamic constraints using a metaheuristic algorithm

  • Grzywinski, Maksym;Selejdak, Jacek;Dede, Tayfun
    • Steel and Composite Structures
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    • v.33 no.5
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    • pp.747-753
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    • 2019
  • Metaheuristic algorithm is used to solve the weight minimization problem of truss structures considering shape, and sizing design variables. The cross-sectional areas of the line element in trusses are the design variables for size optimization and the changeable joint coordinates are the shape optimization used in this study. The design of plane and spatial truss structures are optimized by metaheuristic technique named Teaching-Learning-Based Optimization (TLBO). Finite element analyses of structures and optimization process are carried out by the computer program visually developed by the authors coded in MATLAB. The four benchmark problems (trusses 2D ten-bar, 3D thirty-seven-bar, 3D seventy-two-bar and 2D two-hundred-bar) taken from literature are optimized and the optimal solution compared the results given by previous studies.

Mathematical Optimization Techniques in Drug Product Design and Process Analysis. Optimization Techniques in Tablet Design (의약품 제조설계 및 조작분석의 최적화에 관한 연구 - 정제제조의 최적화)

  • 김용배
    • YAKHAK HOEJI
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    • v.18 no.1
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    • pp.49-58
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    • 1974
  • Tablet product design problem was structured as constrained optimization problem and subsequently solved by multiple regression analysis and Lagrangian method of optimization. Aluminum flufenamate was the drug chosen and microcrystalline cellulose nad starch were the binder and disintegrant, respectivley. The effect of the binder and disintegrant concentration on tablet hardness, friability, volume, in vitro release rate, and urinary excretion rate of drug in human subjects was recorded. Since a reasonably rapid release rate of drug is generally an important objective in the design of solid dosage form, optimization of this parameter was employed in studying the applicability of constrained optimization to a pharmaceutical product design problem. In addition to finding optimal sitivity analysis studies to such problems was also illustratd. It would appear that prediction of the in vivo t$_{50%}$ response from a knowledge of the incitro t$_{50%}$ response can be made fairly accurately for the tablet system used in this study.

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Critical buckling load optimization of the axially graded layered uniform columns

  • Alkan, Veysel
    • Structural Engineering and Mechanics
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    • v.54 no.4
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    • pp.725-740
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    • 2015
  • This study presents critical buckling load optimization of the axially graded layered uniform columns. In the first place, characteristic equations for the critical buckling loads for all boundary conditions are obtained using the transfer matrix method. Then, for each case, square of this equation is taken as a fitness function together with constraints. Due to explicitly unavailable objective function for the critical buckling loads as a function of segment length and volume fraction of the materials, especially for the column structures with higher segment numbers, initially, prescribed value is assumed for it and then the design variables satisfying constraints are searched using Differential Evolution (DE) optimization method coupled with eigen-value routine. For constraint handling, Exterior Penalty Function formulation is adapted to the optimization cycle. Different boundary conditions are considered. The results reveal that maximum increments in the critical buckling loads are attained about 20% for cantilevered and pinned-pinned end conditions and 18% for clamped-clamped case. Finally, the strongest column structure configurations will be determined. The scientific and statistical results confirmed efficiency, reliability and robustness of the Differential Evolution optimization method and it can be used in the similar problems which especially include transcendental functions.