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Preform design plays an important role in improving the material flow, mechanical properties and reducing defects for forgings with complex shapes. In this paper, a study on shape optimization of preform tools in forging of an airfoil is carried out based on a multi-island genetic algorithm combined with a metamodel technique. An optimal Latin hypercube sampling technique is employed for sampling with the expected coverage of parameter space. Finite element (FE) simulations of multistep forging processes are implemented to obtain the objective function values for evaluating the forging qualities. For facilitating the optimization process, a radial basis function surrogate model is established to predict the responses of the hot forging process to the variation of the preform tool shape. In consideration of the compromise between different optimal objectives, a set of Pareto-optimal solutions are identified by the suggested genetic algorithm to provide more selections. Finally, according to the proposed fitness function, the best solution of multi-objective optimization on the Pareto front is confirmed and the corresponding preform tool shape proves optimal performances with substantially improved forging qualities via FE validation. 相似文献
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This study proposes a methodology to solve the integrated problems of selection and scheduling of the exclusive bus lane. The selection problem intends to determine which roads (links) should have a lane reserved for buses while the scheduling problem intends to find the time period of the application. It is formulated as a bi-objective optimization model that aims to minimize the total travel time of non-bus traffic and buses simultaneously. The proposed model formulation is solved by the hybrid non-dominated sorting genetic algorithm with Paramics. The results show that the proposed methodology is workable. Sets of Pareto solutions are obtained indicating that a trade-off between buses and non-bus traffic for the improvement of the bus transit system is necessary when the exclusive bus lane is applied. This allows the engineer to choose the best solutions that could balance the performance of both modes in a multimode transport system environment to achieve a sustainable transport system. 相似文献
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To determine the minimum velocity required to prevent sedimentation, six different models were proposed to estimate the densimetric Froude number (Fr). The dimensionless parameters of the models were applied along with a combination of the group method of data handling (GMDH) and the multi-target genetic algorithm. Therefore, an evolutionary design of the generalized GMDH was developed using a genetic algorithm with a specific coding scheme so as not to restrict connectivity configurations to abutting layers only. In addition, a new preserving mechanism by the multi-target genetic algorithm was utilized for the Pareto optimization of GMDH. The results indicated that the most accurate model was the one that used the volumetric concentration of sediment (CV), relative hydraulic radius (d/R), dimensionless particle number (Dgr) and overall sediment friction factor (λs) in estimating Fr. Furthermore, the comparison between the proposed method and traditional equations indicated that GMDH is more accurate than existing equations. 相似文献
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Xiaodong Wang Charles Hirsch Zhiyi Liu Shun Kang Chris Lacor 《International journal for numerical methods in engineering》2013,94(2):111-127
The aerodynamic performance of a compressor is highly sensitive to uncertain working conditions. This paper presents an efficient robust aerodynamic optimization method on the basis of nondeterministic computational fluid dynamic (CFD) simulation and multi‐objective genetic algorithm (MOGA). A nonintrusive polynomial chaos method is used in conjunction with an existing well‐verified CFD module to quantify the uncertainty propagation in the flow field. This method is validated by comparing with a Monte Carlo method through full 3D CFD simulations on an axial compressor (National Aeronautics and Space Administration rotor 37). On the basis of the validation, the nondeterministic CFD is coupled with a surrogate‐based MOGA to search for the Pareto front. A practical engineering application is implemented to the robust aerodynamic optimization of rotor 37 under random outlet static pressure. Two curve angles and two sweep angles at tip and hub are used as design variables. Convergence analysis shows that the surrogate‐based MOGA can obtain the Pareto front properly. Significant improvements of both mean and variance of the efficiency are achieved by the robust optimization. The comparison of the robust optimization results with that of the initial design, and a deterministic optimization demonstrate that the proposed method can be applied to turbomachinery successfully. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
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In this paper, we investigate three recently proposed multi-objective optimization algorithms with respect to their application
to a design-optimization task in fluid dynamics. The usual approach to render optimization problems is to accumulate multiple
objectives into one objective by a linear combination and optimize the resulting single-objective problem. This has severe
drawbacks such that full information about design alternatives will not become visible. The multi-objective optimization algorithms
NSGA-II, SPEA2 and Femo are successfully applied to a demanding shape optimizing problem in fluid dynamics. The algorithm
performance will be compared on the basis of the results obtained. 相似文献
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遗传算法在真空科学优化计算中的应用 总被引：1，自引：0，他引：1
利用智能优化理论,采用改进的遗传算法,研究了遗传法在真空科学优化计算中的应用。并以真空冷冻干燥工艺条件的优化为例,采用该算法进行了优化计算。优化结果与用单纯形法所求得的最优解相比较,结果相差不大。 相似文献
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This article presents a multi-objective design optimization study of a vehicle suspension system with passive variable stiffness and active damping. Design of suspension systems is particularly challenging when the effective mass of the vehicle is subject to considerable variation during service. Perfectly maintaining the suspension performance under the variable load typically requires a controlled actuator to emulate variable stiffness. This is typically done through a hydraulic or pneumatic system, which can be too costly for small/medium pick-up trucks. The system in this article employs two springs with an offset to the second spring so that it engages during large deformation only, thereby providing passive variable stiffness without expensive hydraulics. The system damping is assumed to be controlled via variable viscosity magnetizable fluid, which can be implemented in a compact, low-power set-up. Performance indices from the literature are evaluated at minimum and maximum weight, and regarded as objectives in a multi-objective problem. As the individual objectives are prone to having local optima, the multi-objective problem is prone to having a disjointed Pareto-space. To deal with this issue, a modification is proposed to a multi-objective genetic algorithm. The algorithm performance is investigated via analytical test functions as well as the design case of the suspension system. 相似文献
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遗传算法在响应曲面拟合中的应用 总被引：1，自引：0，他引：1
响应曲面方法（RSM）是一种重要的实验设计优化方法,但是当影响因素和响应输出之间的关系异常复杂时,RSM难以拟合影响因素和响应输出之间的响应曲面.遗传算法（GAs）是一种借鉴生物界自然选择和进化发展起来的高度并行、随机、自适应搜索算法,具有强大的搜索能力.本文将遗传算法引入RSM,通过对遗传算法各参数的设计和改进,克服了传统遗传算法易局部收敛的问题. 相似文献
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Optimization methods have been widely used in practical engineering, with search efficiency and global search ability being the main evaluation criteria. In this article, the Bezier curve equivalent recursion is used in a genetic algorithm (GA) to realize the variant space search to improve the search efficiency and global search ability. The parameters related to this method are investigated by an optimization test of the simple curve approximation, which is then used for optimization designs of supersonic and transonic profiles. The results show that the GA can be improved if the variant space search method is added. 相似文献
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A. A. Groenwold N. Stander J. A. Snyman 《International journal for numerical methods in engineering》1999,44(6):749-766
A regional genetic algorithm (R‐GA) is used for the discrete optimal design of truss structures. The chromosomes are selected from a sub‐region centred on the continuous optimum. This approach replaces genetic rebirth as previously proposed by other authors, thereby significantly reducing computational costs. As a pure discrete method, the R‐GA method does not require heuristic arguments or approximations. This makes the algorithm highly effective when buckling and slenderness constraints with scatter in the data are introduced. A large set of numerical test examples is used to illustrate the capabilities of the method. The algorithm is shown to be effective and robust, making it suitable for the optimal design of very large truss structures. Copyright © 1999 John Wiley & Sons, Ltd. 相似文献
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Soon Yu Woon Liyong Tong Osvaldo M. Querin Grant P. Steven 《International journal for numerical methods in engineering》2003,58(4):643-660
Shape optimization through a genetic algorithm (GA) using discrete boundary steps and the fixed‐grid (FG) finite‐element analysis (FEA) concept was recently introduced by the authors. In this paper, algorithms based on knowledge specific to the FG method with the GA‐based shape optimization (FGGA) method are introduced that greatly increase its computational efficiency. These knowledge‐based algorithms exploit the information inherent in the system at any given instance in the evolution such as string structure and fitness gradient to self‐adapt the string length, population size and step magnitude. Other non‐adaptive algorithms such as string grouping and deterministic local searches are also introduced to reduce the number of FEA calls. These algorithms were applied to two examples and their effects quantified. The examples show that these algorithms are highly effective in reducing the number of FEA calls required hence significantly improving the computational efficiency of the FGGA shape optimization method. Copyright © 2003 John Wiley & Sons, Ltd. 相似文献
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Multi-material topology optimization enables potential design possibilities in the multiphysics and structural designing fields. In this article, a bi-level hierarchical optimization method is introduced to address the multi-material design of compliant mechanisms. The hierarchical optimization develops decomposition approaches allowing the original complex multi-material optimization problem to be reduced to set of low-order single-material optimization sub-problems. The solution of the complex multi-material problem is found as a vector of the single-material sub-problems solutions. All the local sub-problems are solved with the solid isotropic material with penalization method independently, and a stiffness spreading technique is worked out to coordinate components of the global solution of the original problem. Several numerical examples are presented to demonstrate the validity of this method. 相似文献
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基于遗传算法的线性两自由度隔振器的瞬态最优设计 总被引：1，自引：2，他引：1
线性两自由度隔振器的瞬态最优设计问题是一类很难求解的非线性规划问题。本文提出一个简单实用的小生境混合遗传算法,避开繁琐的动力灵敏度分析,有效地进行隔振器的瞬态优化设计。一个仿真算例验证了算法的有效性和可行性。 相似文献
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带时间窗车辆路径问题的并行遗传算法 总被引：1，自引：0，他引：1
采用并行遗传算法研究了带时间窗限制的车辆路径问题.通过设计并行算法和交叉、变异等算子提高了算法的计算效率和性能.通过计算若干benchmark问题,验证了模型的有效性. 相似文献
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The structural topology optimization approach can be used to generate compliant mechanisms for some desired input–output requirements. The success of the optimization depends on the structural geometry representation scheme used. In this paper, a novel representation scheme is proposed. The representation scheme is characterized by pairs of curves that are used to connect Input/Ouput (I/O) regions of the structure. Each pair of curves includes a normal curve and a fat curve. The areas bounded by the pair of curves define the material distribution between them. All I/O regions are connected to one another (either directly or indirectly) by pairs of curves in order to form one single connected load-bearing structure. A genetic algorithm for constrained and multiobjective optimization is then applied with the representation scheme of the structure in the form of a graph. Simulation results from a displacement inverter and a displacement redirector indicate that the presented representation scheme is appropriate. 相似文献
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零件生产加工过程中,由于各加工特征有多个加工工艺而不同工艺方法又有不同的机器选择,以及受工艺约束的工序特征排序问题,使得柔性工艺规划问题具有NP难特性.通过对可选工序和机器进行分段编码;并用约束调整算法解决受工艺约束的工序排序问题;对于问题的多目标特性,采用随机权重来设置适应度函数,用外部精英保留策略并引入k-means聚类算法裁剪精英集来保持群体多样性,该方法通过该混合遗传算法的交差,变异等操作,能有效解决受工序约束的多工艺路线的优化与决策问题.以实例的形式论证了该算法在求解柔性工艺规划问题的有效可行性. 相似文献