Reliability-based robust multi-objective optimization applied to engineering system design

Lobato, Fran Sérgio; Silva, Marcio Aurélio da; Cavalini, Aldemir Ap; Steffen, Valder

doi:10.1080/0305215x.2019.1577413

Cited by 32 publications

(8 citation statements)

References 39 publications

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“…4.2.2 Welded beam. This problem consists of a beam submitted to a force F applied to one of its ends that is to be welded to another structural component satisfying the conditions of stability and the design limitations (Castro, 2001;Lobato and Steffen, 2007;Lobato, 2008). The four design variables, namely the thickness of the weld (h), the length of the weld (l ), the width of the beam (t) and the thickness of the beam (b) are shown in Figure 12 (Castro, 2001).…”

Section: Engineering Test Casesmentioning

confidence: 99%

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A novel multi-objective optimization method with local search scheme using shuffled complex evolution applied to mechanical engineering problems

Lobato

Libotte

Platt

2022

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PurposeIn this work, the multi-objective optimization shuffled complex evolution is proposed. The algorithm is based on the extension of shuffled complex evolution, by incorporating two classical operators into the original algorithm: the rank ordering and crowding distance. In order to accelerate the convergence process, a Local Search strategy based on the generation of potential candidates by using Latin Hypercube method is also proposed.Design/methodology/approachThe multi-objective optimization shuffled complex evolution is used to accelerate the convergence process and to reduce the number of objective function evaluations.FindingsIn general, the proposed methodology was able to solve a classical mechanical engineering problem with different characteristics. From a statistical point of view, we demonstrated that differences may exist between the proposed methodology and other evolutionary strategies concerning two different metrics (convergence and diversity), for a class of benchmark functions (ZDT functions).Originality/valueThe development of a new numerical method to solve multi-objective optimization problems is the major contribution.

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Section: Engineering Test Casesmentioning

confidence: 99%

“…4.2.1 Beam with Section I. This traditional engineering problem considers a beam with section I subject to vertical (P) and horizontal (Q) load applied at the midpoint of the beam, as presented in Figure 10 (Castro, 2001;Lobato and Steffen, 2007;Lobato, 2008):…”

Section: Engineering Test Casesmentioning

confidence: 99%

A novel multi-objective optimization method with local search scheme using shuffled complex evolution applied to mechanical engineering problems

Lobato

Libotte

Platt

2022

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“…Diante do que foi apresentado, este trabalho tem como objetivo a determinação da geometria de hidrociclones considerando análise de incertezas no contexto multiobjetivo. Para essa finalidade, o algoritmo MODE (Multi-objective Optimization Differential Evolution), proposto por Lobato (2008), é associado à técnica de inserção de confiabilidade IRA (Inverse Reliability Analysis), proposto por Du (2005), para obter hidrociclones com bons desempenhos nos quesitos separação, concentração e consumo energético. Além disso, deseja-se ainda avaliar os efeitos da inserção de confiabilidade nos resultados da otimização multi-objetivo.…”

Section: Introductionunclassified

“…Caso G(u*) ≤ 0, então a probabilidade de x atender à restrição é maior ou igual à confiabilidade alvo, caso contrário essa probabilidade é menor que a confiabilidade desejada. É importante destacar Brazilian Journal of Development,Curitiba, v.8, n.2, p. 15195-15208 , feb., 2022. que, diferentes tipos de distribuição de probabilidades podem ser convertidos em uma distribuição padrão, a saber, a normal, conforme descrito por Rosenblatt (1952).2.3 MODE+IRAO algoritmo de Evolução Diferencial é uma técnica proposta por Storn e Price (1997) e que se diferencia dos demais métodos heurísticos pela forma como é feita a operação de cruzamento, a saber, via realização de operações vetoriais entre os indivíduos da população.Devido ao sucesso alcançado por esse algoritmo,Lobato (2008) propôs a sua extensão para o contexto multi-objetivo -MODE (Multi-Objective Optimization Differential Evolution). Em linhas gerais, essa estratégia faz uso de um sistema de classificação dos indivíduos baseado em ranks via critério de dominância de Pareto associado a um operador de distância de multidão para priorizar a manutenção na população de indivíduos mais distantes dos demais, favorecendo, assim, a diversidade das soluções.No contexto da confiabilidade, o algoritmo MODE é associado ao IRA para fins de análise de confiabiliadade no contexto multi-objetivo.…”

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Otimização multi-objetivo baseada em confiabilidade para o projeto de hidrociclones / Reliability-based multi-objective optimization for hydrocyclone design

Garcia¹,

Kyriakidis²,

Lobato³

et al. 2022

BJDV

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Hidrociclones são equipamentos usados para realizar separações sólido-líquido através da ação centrífuga. O desempenho desses separadores é altamente dependente de sua geometria e pode ser quantificado através de respostas como eficiência total, razão de líquido, número de Euler, diâmetro de corte e concentração volumétrica do underflow. Em algumas aplicações é desejável que o hidrociclone apresente bons desempenhos em todas essas respostas, contudo algumas delas apresentam comportamento conflitante

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“…Reliability is the probability that a product will not fail. The failure probability of the product is closely related with the uncertainty of design parameters [16,17]. The traditional optimization design is usually performed without considering the uncertainty of input variables, which may lead to failure of the optimization results in practical application.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Reliability-Based Optimization of Control Arm Using MCS and NSGA-II Coupled with Entropy Weighted GRA

et al. 2021

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Lightweight design is one of the important ways to reduce automobile fuel consumption and exhaust emissions. At the same time, the fatigue life of automobile parts also greatly affects vehicle safety. This paper proposes a multi-objective reliability optimization method by integrating Monte Carlo simulation (MCS) with the NSGA-II algorithm coupled with entropy weighted grey relational analysis (GRA) for lightweight design of the lower control arm of automobile Macpherson suspension. The dynamic load histories of the control arm were extracted through dynamic simulations of a rigid-flexible coupling vehicle model on virtual proving ground. Then, the nominal stress method was used to predict its fatigue life. Six design variables were defined to describe the geometric dimension of the control arm, while mass and fatigue life were taken as optimization objectives. The multi-objective optimization design of the control arm was carried out based on the Kriging surrogate model and NSGA-II algorithm. Aiming at the uncertainty of design variables, the reliability constraint was added to the multi-objective optimization to improve the reliability of the fatigue life of the control arm. The optimal design of the control arm was determined from Pareto solutions by entropy weighted grey relational analysis (GRA). The optimization results show that the mass of the control arm was reduced by 4.1% and the fatigue life was increased by 215.8% while its reliability increased by 7.8%. The proposed multi-objective reliability optimization method proved to be feasible and effective for lightweight design of a suspension control arm.

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Reliability-based robust multi-objective optimization applied to engineering system design

Cited by 32 publications

References 39 publications

A novel multi-objective optimization method with local search scheme using shuffled complex evolution applied to mechanical engineering problems

A novel multi-objective optimization method with local search scheme using shuffled complex evolution applied to mechanical engineering problems

Otimização multi-objetivo baseada em confiabilidade para o projeto de hidrociclones / Reliability-based multi-objective optimization for hydrocyclone design

Multi-Objective Reliability-Based Optimization of Control Arm Using MCS and NSGA-II Coupled with Entropy Weighted GRA

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