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The focus of this paper is concentrated on multi-disciplinary and multi-objective optimization for thin walled beam systems considering safety, normal mode, static loading-bearing and weight, in which the uncertainties of the parameters are described via intervals. The size and shape of the cross-section are treated as design parameters during optimization. Considering the lightweight and safety, the design problem is formulated with two individual objectives to measure structural weight and maximum energy absorption, respectively, constrained by the average force, normal mode and maximum stress. The optimization problem with uncertainties is further transformed into a deterministic optimization based on interval number programming. The approximation models, coupled with the design of experiment (DOE) technique, are employed to construct objective functions and constraints. The uncertain optimization problem characterized with these approximation models is performed and applied to a practical thin walled beam design problems. 相似文献
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电动汽车租赁行业迅速发展。为满足消费者和企业的综合需求,研究了面向电动汽车租赁的多目标服务组合优化设计方法。借助模糊理论确定各服务项权重,引入失望理论描述顾客的欣喜与失望感知以计算感知绩效,建立方案成本、相容度、市场竞争指数的计算方法,最终提出顾客感知绩效最大、成本最低、方案相容最优、市场竞争力最大的电动汽车租赁多目标服务组合优化设计模型。通过一种面向多阶段的多目标权重确定法对不同阶段的多目标决策设定权重。最后,通过实际项目案例对模型进行有效性验证,针对推广市场的不同阶段分别制定服务组合套餐,目标优化结果显著,为电动汽车租赁企业在服务设计方面提供了科学有效的决策方法。 相似文献
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提出一种新颖的圆形多胞复合填充结构,该结构采用蜂窝和泡沫两类材料的交错复合填充。采用实验验证与数值研究相结合的方法,系统地研究了蜂窝和泡沫材料在全填充、部分填充及交互填充结构中的耐撞性。研究结果表明,针对单一材料填充的多胞圆管,部分填充结构比全填充结构具有更好的耐撞性能,其中,环形蜂窝填充结构(H40)和中心泡沫填充结构(F01)具有更优异的能量吸收特性。针对双材料复合填充的多胞圆管,则是中心泡沫填充与环形蜂窝填充的复合结构(F01H40)具有最佳的耐撞吸能性。最后,进一步结合Kriging近似技术与粒子群数值优化方法,对复合填充结构进行多目标优化设计,探索其最优耐撞性与最优参数匹配。结果表明,环形蜂窝部分填充结构(H40)、中心泡沫填充与环形蜂窝填充的复合全填充结构(F01H40)具有最优的耐撞性能。 相似文献
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Electric vehicles (EVs) are recognized as one of the most promising technologies worldwide to address the fossil fuel energy resource crisis and environmental pollution. As the initial work of EV charging station (EVCS) construction, site selection plays a vital role in its whole life cycle. In this paper, a multi-objective optimization model for the location layout of EVCSs is established when considering various factors such as user demand, investment cost, soil locations, the emergency charging mileage limit, the actual road condition and service network reliability. The model takes the minimum investment cost and the minimum user charging cost as the dual objectives. On the basis of satisfying the user’s charging demand and the capacity constraints of EVCSs, the redundant design of the charging pile and station is considered to ensure the reliability of the service network. In the allocation of user charging demand, in this paper, two factors of time and distance are considered, and the equal time load distance method is adopted to distribute traffic flow under the limitation of emergency charging mileage. When calculating the average travel speed of a road section, an accounting method based on the land price level is proposed considering the congestion. Then, the linear weighting method is applied to normalizing the multi-objective function, and the genetic algorithm is employed to solve the problem. Finally, a computational experiment is presented to demonstrate the applicability and effectiveness of the proposed approach. The results show that the proposed approach is a useful, practical, and effective way to find the optimal location of EVCSs. 相似文献
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通过SRAC对汽车悬架进行不同情形的有限元优化分析,揭示了汽车主要零件-汽车悬架受力在不同情形下的分布规律,对悬架臂的尺寸优化设计。 相似文献
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目的 降低冷链物流配送成本的同时,保证客户体验及碳排放达到企业要求。方法 综合考虑运输距离、客户软时间窗约束、碳排放、生鲜变质等因素,以制冷成本及对配送时间惩罚成本在内的总成本最低、碳排放量最低、生鲜产品新鲜度最高为目标,建立多目标生鲜配送路径优化模型,并设计模拟退火算法,以北京某冷链物流企业为例进行求解验证。结果 得出生鲜配送方案,通过配送模式对比表明多中心半开放式在降本和缩短路径长度方面更具优势,其中运输总费用和车辆行驶总距离相比于单中心独立配送模式分别降低了8.41%和36.36%。结论 需求不确定下,合理决策路由可在达到企业对生鲜产品新鲜度及碳排放标准的同时,有效降低配送成本。 相似文献
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目的 为了进一步优化航材库存结构,解决多目标航材分配问题,提高航材保障工作决策的效率.方法 建立基于费用和分配满意度的多目标航材分配模型,运用先进的群体智能算法——蝗虫算法求解.结果 算例分析表明,在3种求解算法中,蝗虫算法所求出来的解,既使得航材分配过程中所需成本最低,又保证了航材股满意度处于较高水平.同时,将算法运行10次,蝗虫算法的求解时间平均值和方差分别为4.01 ms和11.5 ms,明显优于传统的群智能算法粒子群和NSGA-Ⅱ算法的求解效率.结论 蝗虫算法能够有效地解决多目标航材分配问题,对于优化航材库存,平衡航材数量具有重要的现实意义. 相似文献
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目的 针对纸浆浓度PID控制系统在时滞性、稳定性、耦合性方面的不足,提出一种基于多目标优化的纸浆浓度PID控制方法.方法 对纸浆生产工艺进行分析,结合纸浆浓度PID控制系统,设定多属性的决策变量,建立对应的目标函数和约束条件;从质量、产量、成本、环境等4个方面对纸浆浓度PID控制过程进行多目标优化,构建基于多目标优化的纸浆浓度PID控制模型;采用改进量子粒子群算法对多目标优化模型进行求解,获得Pareto最优纸浆浓度控制方案;将建模方法、优化算法、优选方法进行耦合,从而形成"建模-求解-优选"全过程的纸浆浓度控制方法.结果 通过对纸浆浓度控制优化前后的决策变量进行比较分析可知,多目标优化PID控制方法在评价指标方面满足了质优、高产、低耗的多目标优化的可控性要求;相较于传统PID控制方法,IPSO-PID控制方法的响应速度更快,具有更好的鲁棒性;在PID参数优化方面,文中的优化模型整定控制参数在0.05 s内达到稳态阶段,稳态误差更低,具有更好的稳定性.结论 在保证系统鲁棒性的同时,基于多目标优化算法的纸浆浓度PID控制系统可实现对纸浆浓度的精确性和稳定性控制,更好地满足实际工业生产的要求,确保纸张质量的品质. 相似文献
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随着外卖行业的不断发展,外卖配送的路径优化问题已引起学者们的广泛关注。但现有研究未将骑手的目标考虑在内,且未考虑动态场景下多目标如何设定权重的问题。因此,本文对外卖配送路径的多目标实时优化进行深入研究。建立多目标外卖配送路径优化模型。该模型不仅考虑订单履行时间、平台利润和骑手服务质量3个常用的目标,另外增加骑手等待时间和骑手空驶距离这两个目标,充分将外卖平台、顾客和骑手的目标综合考虑。设计动态调整权重的多目标外卖配送路径启发式算法,解决动态场景下多目标权重如何设定的问题。通过外卖配送的实时数据进行算例分析。结果表明,本文提出的算法可以有效对多目标的外卖配送问题进行实时路径优化,且订单的密集程度对骑手等待时间和订单履行时间有直接的影响。 相似文献
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区间参数结构动力优化的改进方法 总被引:1,自引:0,他引:1
针对区间参数结构,提出一种改进的动力响应的区间优化方法。由于区间优化问题一般要比确定性优化问题的求解复杂得多,因此,通过优化结构动力响应区间值的上界,将区间优化问题转化为近似的确定性优化问题。为了得到结构动力响应更加准确的区间值,把结构动力响应Taylor展开式中的一阶导数也看成区间的,这样得到的区间值能近似包含精确值。在区间优化方法中,设计变量的中值和半径都被选为优化变量,可以得到比传统确定性优化方法更多的优化信息。把该方法应用于典型刚架结构,优化结果表明,区间优化方法不仅能得到与传统优化方法大致相当的设计变量最优值,还能得到实际问题中当设计变量取不到最优值而有微小变化时,目标函数值的一个变化范围。 相似文献
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M. Premkumar Pradeep Jangir B. Santhosh Kumar Mohammad A. Alqudah Kottakkaran Sooppy Nisar 《计算机、材料和连续体(英文)》2022,70(2):2435-2458
The first step in the design phase of the Brushless Direct Current (BLDC) motor is the formulation of the mathematical framework and is often used due to its analytical structure. Therefore, the BLDC motor design problem is considered to be an optimization problem. In this paper, the analytical model of the BLDC motor is presented, and it is considered to be a basis for emphasizing the optimization methods. The analytical model used for the experimentation has 78 non-linear equations, two objective functions, five design variables, and six non-linear constraints, so the BLDC motor design problem is considered as highly non-linear in electromagnetic optimization. Multi-objective optimization becomes the forefront of the current research to obtain the global best solution using metaheuristic techniques. The bio-inspired multi-objective grey wolf optimizer (MOGWO) is presented in this paper, and it is formulated based on Pareto optimality, dominance, and archiving external. The performance of the MOGWO is verified on standard multi-objective unconstraint benchmark functions and applied to the BLDC motor design problem. The results proved that the proposed MOGWO algorithm could handle nonlinear constraints in electromagnetic optimization problems. The performance comparison in terms of Generational Distance, inversion GD, Hypervolume-matrix, scattered-matrix, and coverage metrics proves that the MOGWO algorithm can provide the best solution compared to other selected algorithms. The source code of this paper is backed up with extra online support at and . 相似文献
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