Multi-objective topology optimization using evolutionary algorithms

Kunakote, Tawatchai; Bureerat, Sujin

doi:10.1080/0305215x.2010.502935

Cited by 85 publications

(55 citation statements)

References 20 publications

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“…Two popular, well known topological methods are the solid isotropic material with penalization (SIMP) approach and the homogenization method, which use gradient-based optimizers. Later, an alternative optimizer is evolutionary algorithms due to the fact they are robust, simple to use, derivative-free, and free from intermediate pseudo densities [8]. Complicated problems, such as partial topology, simultaneous topology, shape, and sizing optimization, can be performed within one optimization run [3,8,16,17] by using such algorithms.…”

Section: Topological Designs With Ground Element Filteringmentioning

confidence: 99%

“…The second question arises due to an opposition-based concept that could potentially improve the search performance of the evolutionary algorithm (EA) [4][5][6][7]; the multi-objective population-based incremental learning (MPBIL) was the best optimizer [8]. Additionally, it has been demonstrated that the opposition-based concept could improve population-based incremental learning (PBIL) performance for a single objective, which is called the opposition-based concept PBIL(OPBIL) [9], whereas the multi-objective optimization is called opposite-based, multi-objective, population-based incremental learning (OMPBIL) [3].…”

Section: Introductionmentioning

confidence: 99%

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Topology Optimisation Using MPBILs and Multi-Grid Ground Element

Sleesongsom

Bureerat

2018

Applied Sciences

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This paper aims to study the comparative performance of original multi-objective population-based incremental learning (MPBIL) and three improvements of MPBIL. The first improvement of original MPBIL is an opposite-based concept, whereas the second and third method enhance the performance of MPBIL using the multi and adaptive learning rate, respectively. Four classic multi-objective structural topology optimization problems are used for testing the performance. Furthermore, these topology optimization problems are improved by the method of multiple resolutions of ground elements, which is called a multi-grid approach (MG). Multi-objective design problems with MG design variables are then posed and tackled by the traditional MPBIL and its improved variants. The results show that using MPBIL with opposite-based concept and MG approach can outperform other MPBIL versions.

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Section: Topological Designs With Ground Element Filteringmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Topology Optimisation Using MPBILs and Multi-Grid Ground Element

Sleesongsom

Bureerat

2018

Applied Sciences

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“…With the increase in crossover factor Cr, more changes are introduced into the new generation. The traditional method cannot guarantee precedence constraints; 25 this article proposes a new program to well inherit good structures from the target individual and to yield a better mutant individual, an improved crossover operator is given as follows(illustrated by an example in Table 6):…”

Section: Hdde Algorithmmentioning

confidence: 99%

A novel hybrid discrete differential evolution algorithm for workingsteps sequencing in multi-channel turn-milling complex machining

Shi

Qiao

Zhu

2015

Advances in Mechanical Engineering

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To address the problem of workingsteps sequencing in multi-channel turn-milling complex machining, a novel hybrid optimization algorithm titled hybrid discrete differential evolution has been proposed, which improves the algorithm to achieve better results for the workingsteps sequencing problem. The main thrust of this article is twofold: (1) to analyze the characteristics of synchronous machining in multi-channel turn-milling complex machining and their constraints, and to propose a zero-wait micro-resource allocation strategy; (2) to develop a hybrid discrete differential evolution algorithm for process planning in multi-channel turn-milling complex machining, and to describe in detail about the operation of crossover, mutation, and selection. Then, analysis of variance has been used to investigate the contribution and effects of variables (parameters) in hybrid discrete differential evolution, so the optimal parameters can be obtained. Finally, a comparison of the performance and efficiency between the proposed algorithm and the classical differential evolution algorithm is made. And experimental results show that the hybrid discrete differential evolution algorithm is good at solving the sequencing problem, and the results approximate the optimum expectation.

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“…Pareto 前沿的智能正则约束法。罗震等 [9] 按经验法给定各工况的权重系数，基于带权重的折衷规划法 (含有加权系数的 q 范数)和带惩罚的固体各向同性材料插值法(Solid isotropic material with penalization for intermediate densities, SIMP)插值模型对多刚度结构拓扑优化问题进行了研究。兰凤崇等 [10] 采用层次分析法来确定各工况的最优权重系数，运用折衷规划法构建综合目标函数，对多工况车身结构进行了优化设计。张志飞等 [11] 以灰色综合关联分析确定子目标的权重系数，以折衷规划法归一化子目标建立综合目标函数，对多目标的汽车悬架控制臂进行了优化研究。利用加权和方法进行优化，方法易于实现，但是权重系数体现了各子目标在结构中的重要性，不同的权重系数会得到不同的优化结果。目前还没有系统确定各工况权重系数的方法 [10] ，如何合理的选取权重系数仍待研究。进化算法 [2,[12][13] 是另一种常用的多目标优化问题求解方法。MADEIRA 等 [14] 和 CARDILLO 等 [15] 分别采用遗传算法对多刚度结构拓扑优化问题进行了优化。另外， …”

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A New Solving Method of the Compliance Topology Optimization Problem of Continuum Structures under Multiple Load Cases

Yu¹

2018

JME

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Abstract：Most of engineering structures work under multiple load cases, and topology compliance minimization under multiple load cases are of important engineering value. A new compliance topology optimization method of continuum structures under multiple load cases with a volume constraint is proposed. Firstly, being referred to the bound formulation method, original multiple objective functions dealing with structural compliance under multiple load cases are transferred to multiple constraints by using a bound variable, and a novel quadratic function of the bound variable is treated as a new objective function. At the same time, being integrated with a varied volume limit scheme, a novel and equivalent approximate topology model is constructed. Then, convex and separable quadratic approximate functions for the volume and structural compliance under multiple load cases, are formed, based on the rational approximation for material properties (RAMP) and the method of moving asymptotes (MMA). The approximate optimization model is solved by adopting a smooth dual algorithm, and a new compliance topology optimization procedure, possessing convergence, is proposed. It is concluded from given examples that the proposed method is higher efficient for generating a same optimal topology, or may obtain a more optimal topology than the existed methods; and an optimal topology with clear 0/1 distribution, may robustly be obtained by the proposed method. Key words：structural topology optimization；multiple load cases；structural compliance；dual algorithm；multiple objective optimization * 国家自然科学基金(11372055, 11772070)和工程车辆轻量化与可靠性技术湖南省高校重点实验室(长沙理工大学)开放基金(2013KFJJ03)资助项目。20170612 收到初稿，20170919 收到修改稿

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Multi-objective topology optimization using evolutionary algorithms

Cited by 85 publications

References 20 publications

Topology Optimisation Using MPBILs and Multi-Grid Ground Element

Topology Optimisation Using MPBILs and Multi-Grid Ground Element

A novel hybrid discrete differential evolution algorithm for workingsteps sequencing in multi-channel turn-milling complex machining

A New Solving Method of the Compliance Topology Optimization Problem of Continuum Structures under Multiple Load Cases

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