A random search for discrete robust design optimization of linear-elastic steel frames under interval parametric uncertainty

Do, Bach; Ohsaki, Makoto

doi:10.1016/j.compstruc.2021.106506

Cited by 13 publications

(5 citation statements)

References 49 publications

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“…Calculate the mutual compliance coefficient c pq and obtain objective function using formulas (14). (c) Calculate the sensitivity information according to equations ( 28) and (30).…”

Section: Processmentioning

confidence: 99%

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Robust topology optimization of truss-like continuum structures under uncertain loads based on cloud model

Guo,

Zhou,

Shi

2023

Mathematics and Mechanics of Solids

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The traditional structural performance may be seriously degraded due to applied indeterministic cases. A novel framework for robust topology optimization of truss-like continuum considering uncertain loads is presented. The robust optimization formula is constructed as minimizing the weighted sum of expectancy and standard variance of structural compliance with volume constraints. In this framework, both the magnitude and direction of applied loads are uncertain and independent. Truss-like continuum provides the topology optimal structure theoretically. Based on the classic truss-like optimization method, the statistical moments of compliance are accurately evaluated utilizing a bivariate cloud model tool. An effective strategy based on linear decoupling is reported to largely reduce the total number of finite element analysis. The optimization is achieved with gradient-based mathematic programming. Several numerical examples demonstrate a better structural robust performance obtained by the proposed algorithm than the traditional one.

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“…Calculate the mutual compliance coefficient c pq and obtain objective function using formulas (14). (c) Calculate the sensitivity information according to equations ( 28) and (30).…”

Section: Processmentioning

confidence: 99%

“…Two classic types of theoretical models in RTO can be distinguished. One way is the non-probabilistic convex model, which is committed to minimizing the objective function values in the worst-case scenario [12][13][14][15]. The other, called the average approach, is to minimize the expectancy of the structural performance [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Robust topology optimization of truss-like continuum structures under uncertain loads based on cloud model

Guo,

Zhou,

Shi

2023

Mathematics and Mechanics of Solids

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“…In this section, the validity of IPSO-MS is evaluated on both test systems. In addition, the parameters of PSO are confirmed through random search (Do and Ohsaki, 2021 ), which are shown in Table 1 .…”

Section: Case Studymentioning

confidence: 99%

Scenario-Based Distributionally Robust Unit Commitment Optimization Involving Cooperative Interaction with Robots

et al. 2022

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With the increasing penetration of renewable energy, uncertainty has become the main challenge of power systems operation. Fortunately, system operators could deal with the uncertainty by adopting stochastic optimization (SO), robust optimization (RO) and distributionally robust optimization (DRO). However, choosing a good decision takes much experience, which can be difficult when system operators are inexperienced or there are staff shortages. In this paper, a decision-making approach containing robotic assistance is proposed. First, advanced clustering and reduction methods are used to obtain the scenarios of renewable generation, thus constructing a scenario-based ambiguity set of distributionally robust unit commitment (DR-UC). Second, a DR-UC model is built according to the above time-series ambiguity set, which is solved by a hybrid algorithm containing improved particle swarm optimization (IPSO) and mathematical solver. Third, the above model and solution algorithm are imported into robots that assist in decision making. Finally, the validity of this research is demonstrated by a series of experiments on two IEEE test systems.

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“…As HVI(𝐟|Ω, 𝐟 R ) and  2 (𝐬) are functions of 𝐬, and 𝐫 only appears in  1,1 (𝐬, 𝐫) and  1,2 (𝐬, 𝐫), an optimization strategy that couples a random sampling method with simulated annealing is developed for solving problem (12). This strategy is an extension of a two-stage random search proposed by the authors [40], which includes a stage of determining surrounding each of the current Pareto-optimal solutions, which can be regarded as a neighborhood search. In fact, each integer element of every Pareto-optimal solution is randomly increased or decreased by an integer value such as 1, 2, 3, or 4.…”

Section: Maximizing the Acquisition Functionsmentioning

confidence: 99%

Bayesian optimization for robust design of steel frames with joint and individual probabilistic constraints

Ohsaki

Yamakawa

2021

Engineering Structures

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A random search for discrete robust design optimization of linear-elastic steel frames under interval parametric uncertainty

Cited by 13 publications

References 49 publications

Robust topology optimization of truss-like continuum structures under uncertain loads based on cloud model

Robust topology optimization of truss-like continuum structures under uncertain loads based on cloud model

Scenario-Based Distributionally Robust Unit Commitment Optimization Involving Cooperative Interaction with Robots

Bayesian optimization for robust design of steel frames with joint and individual probabilistic constraints

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