• 제목/요약/키워드: Optimization constraints

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Dynamic mix design optimization of high-performance concrete

  • Ziaei-Nia, Ali;Shariati, Mahdi;Salehabadi, Elnaz
    • Steel and Composite Structures
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    • 제29권1호
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    • pp.67-75
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    • 2018
  • High performance concrete (HPC) depends on various parameters such as the type of cement, aggregate and water reducer amount. Generally, the ready concrete company in various regions according to the requirements and costs, mix design of concrete as well as type of cement, aggregates, and, amount of other components will vary as a result of moment decisions or dynamic optimization, though the ideal conditions will be more applicable for the design of mix proportion of concrete. This study aimed to apply dynamic optimization for mix design of HPC; consequently, the objective function, decision variables, input and output variables and constraints are defined and also the proposed dynamic optimization model is validated by experimental results. Results indicate that dynamic optimization objective function can be defined in such a way that the compressive strength or performance of all constraints is simultaneously examined, so changing any of the variables at each step of the process input and output data changes the dynamic of the process which makes concrete mix design formidable.

유전 알고리즘을 이용한 고속 금형센터의 구조설계 최적화 (Structural Design Optimization of a High Speed Machining Center by Using a Simple Genetic Algorithm)

  • 최영휴;박선균;배병태;이재윤;김태형;박보선
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2000년도 추계학술대회 논문집
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    • pp.1006-1009
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    • 2000
  • In this study, a multi-step optimization technique combined with a simple genetic algorithm is introduced in order to minimize the static compliance, the dynamic compliance, and the weight of a high speed machining center simultaneously. Dimensional thicknesses of the eight structural members on the static force loop are adopted as design variables. The first optimization step is a static design optimization, in which the static compliance and the weight are minimized under some dimensional and safety constraints. The second step is a dynamic design optimization, where the dynamic compliance and the weight are minimized under the same constraints. After optimization, the weight of the moving body only was reduced to 57.75% and the weight of the whole machining center was reduced to 46.2% of the initial design respectively. Both static and dynamic compliances of the optimum design are also in the feasible range even though they were slightly increased than before.

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컴플라이언트 메커니즘의 신뢰성 기반 위상최적설계 (Reliability Based Topology Optimization of Compliant Mechanisms)

  • 임민규;박재용;한석영
    • 한국생산제조학회지
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    • 제19권6호
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    • pp.826-833
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    • 2010
  • Electric-thermal-structural actuated compliant mechanisms are mechanisms onto which electric voltage drop is applied as input instead of force. This mechanism is based on thermal expansion of material while being heated. Compliant mechanisms are designed subjected to electric charge input using BESO(bi-directional evolutionary structural optimization) method. Reliability-based topology optimization (RBTO) is applied to the topology design of actuators. performance measure approach (PMA), which has probabilistic constraints that are formulated in terms of the reliability index, is adopted to evaluate the probabilistic constraints. In this study, BESO method is used to obtain optimal topology of compliant mechanisms from initial design domain. PMA approach is used to evaluate reliability index. The procedure has been tested in numerical applications and compared with the results obtained by other methods to validate these approaches.

최적유효 및 무요전력배분을 위한 신 앨고리즘 (A New Algorithm for Optimal Real and Reactive Power Dispatch)

  • Park, Young-Moon;Lee, Kwang-Yon
    • 대한전기학회논문지
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    • 제32권4호
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    • pp.145-154
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    • 1983
  • This paper presents a new method for optimal real and reactive power dispatch for the economic operation of a power system. Unlike the usual approach of minimizing the transmission loss, this method minimizes the total production cost not only for the real power optimization problem, but also for the reactive power optimization. The control variables are real power generation of units for real power optimization, and reactive power optimization. The constraints are the operating limits on these control variables and the limits on the bus voltages. Methematical models are developed to represent the sensitivity relationships between dependent and control variables for both real and reactive power optimization modules, and thus eliminate the use of B-coefficients. In order to handle many functional inequality constraints, a modified version of the gradient projection method is developed for optimization procedure, and has shown a remarkable advantage in computation efficiency.

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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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    • 제33권5호
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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.

Critical buckling load optimization of the axially graded layered uniform columns

  • Alkan, Veysel
    • Structural Engineering and Mechanics
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    • 제54권4호
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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.

기계 구조의 강건 설계를 위한 최적화 기법의 개발 (Development of an Optimization Technique for Robust Design of Mechanical Structures)

  • 정도현;이병채
    • 대한기계학회논문집A
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    • 제24권1호
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    • pp.215-224
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    • 2000
  • In order to reduce the variation effects of uncertainties in the engineering environments, new robust optimization method, which considers the uncertainties in design process, is proposed. Both design variables and system parameters are considered as random variables about their nominal values. To ensure the robustness of performance function, a new objective is set to minimize the variance of that function. Constraint variations are handled by introducing probability constraints. Probability constraints are solved by the advanced first order second moment (AFOSM) method based on the reliability theory. The proposed robust optimization method has an advantage that the second derivatives of the constraints are not required. The suggested method is examined by solving three examples and the results are compared with those for deterministic case and those available in literature.

덮개 함수를 이용한 강건 최적설계의 제한 조건 단일화 (Unification of Constraints for Robust Optimization Using an Envelope Function)

  • 이정준;정도현;이병채
    • 대한기계학회논문집A
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    • 제26권8호
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    • pp.1719-1726
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    • 2002
  • Design variables and design parameters are rarely deterministic in practice. Robust optimal design takes into consideration of the uncertainties in the design variables and parameters. Robust optimization methodology with probability constraints requires a lot of system analyses fer calculating failure probability of each constraint. By introducing an envelope function to reduce the number of constraints, efficiency of robust optimization techniques can be considerably improved. Through four illustrative examples, it is shown that the number of system analyses is greatly decreased while little differences in the optimum results are observed.

Approximation of reliability constraints by estimating quantile functions

  • Ching, Jianye;Hsu, Wei-Chi
    • Structural Engineering and Mechanics
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    • 제32권1호
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    • pp.127-145
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    • 2009
  • A novel approach is proposed to effectively estimate the quantile functions of normalized performance indices of reliability constraints in a reliability-based optimization (RBO) problem. These quantile functions are not only estimated as functions of exceedance probabilities but also as functions of the design variables of the target RBO problem. Once these quantile functions are obtained, all reliability constraints in the target RBO problem can be transformed into non-probabilistic ordinary ones, and the RBO problem can be solved as if it is an ordinary optimization problem. Two numerical examples are investigated to verify the proposed novel approach. The results show that the approach may be capable of finding approximate solutions that are close to the actual solution of the target RBO problem.

Cooperative Path Planning of Dynamical Multi-Agent Systems Using Differential Flatness Approach

  • Lian, Feng-Li
    • International Journal of Control, Automation, and Systems
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    • 제6권3호
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    • pp.401-412
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    • 2008
  • This paper discusses a design methodology of cooperative path planning for dynamical multi-agent systems with spatial and temporal constraints. The cooperative behavior of the multi-agent systems is specified in terms of the objective function in an optimization formulation. The path of achieving cooperative tasks is then generated by the optimization formulation constructed based on a differential flatness approach. Three scenarios of multi-agent tasking are proposed at the cooperative task planning framework. Given agent dynamics, both spatial and temporal constraints are considered in the path planning. The path planning algorithm first finds trajectory curves in a lower-dimensional space and then parameterizes the curves by a set of B-spline representations. The coefficients of the B-spline curves are further solved by a sequential quadratic programming solver to achieve the optimization objective and satisfy these constraints. Finally, several illustrative examples of cooperative path/task planning are presented.