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A robust multi-objective and multi-physics optimization of multi-physics behavior of microstructure
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作者 Hamda Chagraoui Mohamed Soula Mohamed Guedri 《Journal of Central South University》 SCIE EI CAS CSCD 2016年第12期3225-3238,共14页
A new strategy is presented to solve robust multi-physics multi-objective optimization problem known as improved multi-objective collaborative optimization (IMOCO) and its extension improved multi-objective robust c... A new strategy is presented to solve robust multi-physics multi-objective optimization problem known as improved multi-objective collaborative optimization (IMOCO) and its extension improved multi-objective robust collaborative (IMORCO). In this work, the proposed IMORCO approach combined the IMOCO method, the worst possible point (WPP) constraint cuts and the Genetic algorithm NSGA-II type as an optimizer in order to solve the robust optimization problem of multi-physics of microstructures with uncertainties. The optimization problem is hierarchically decomposed into two levels: a microstructure level, and a disciplines levels, For validation purposes, two examples were selected: a numerical example, and an engineering example of capacitive micro machined ultrasonic transducers (CMUT) type. The obtained results are compared with those obtained from robust non-distributed and distributed optimization approach, non-distributed multi-objective robust optimization (NDMORO) and multi-objective collaborative robust optimization (McRO), respectively. Results obtained from the application of the IMOCO approach to an optimization problem of a CMUT cell have reduced the CPU time by 44% ensuring a Pareto front close to the reference non-distributed multi-objective optimization (NDMO) approach (mahalanobis distance, D2M =0.9503 and overall spread, So=0.2309). In addition, the consideration of robustness in IMORCO approach applied to a CMUT cell of optimization problem under interval uncertainty has reduced the CPU time by 23% keeping a robust Pareto front overlaps with that obtained by the robust NDMORO approach (D2M =10.3869 and So=0.0537). 展开更多
关键词 multi-physics multi-objective optimization robust optimization collaborative optimization non-distributed anddistributed optimization uncertainty interval
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Multi-objective robust secure beamforming for cognitive satellite and UAV networks 被引量:3
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作者 WANG Zining LIN Min +3 位作者 TANG Xiaogang GUO Kefeng HUANG Shuo CHENG Ming 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2021年第4期789-798,共10页
A multi-objective optimization based robust beamforming(BF)scheme is proposed to realize secure transmission in a cognitive satellite and unmanned aerial vehicle(UAV)network.Since the satellite network coexists with t... A multi-objective optimization based robust beamforming(BF)scheme is proposed to realize secure transmission in a cognitive satellite and unmanned aerial vehicle(UAV)network.Since the satellite network coexists with the UAV network,we first consider both achievable secrecy rate maximization and total transmit power minimization,and formulate a multi-objective optimization problem(MOOP)using the weighted Tchebycheff approach.Then,by supposing that only imperfect channel state information based on the angular information is available,we propose a method combining angular discretization with Taylor approximation to transform the non-convex objective function and constraints to the convex ones.Next,we adopt semi-definite programming together with randomization technology to solve the original MOOP and obtain the BF weight vector.Finally,simulation results illustrate that the Pareto optimal trade-off can be achieved,and the superiority of our proposed scheme is confirmed by comparing with the existing BF schemes. 展开更多
关键词 cognitive satellite and unmanned aerial vehicle network(CSUN) multi-objective optimization robust secure beamforming(BF) weighted Tchebycheff approach
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Robust optimization design on impeller of mixed-flow pump 被引量:1
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作者 ZHAO Binjuan LIAO Wenyan +3 位作者 XIE Yuntong HAN Luyao FU Yanxia HUANG Zhongfu 《排灌机械工程学报》 CSCD 北大核心 2021年第7期671-677,共7页
To increase the robustness of the optimization solutions of the mixed-flow pump,the impeller was firstly indirectly parameterized based on the 2D blade design theory.Secondly,the robustness of the optimization solutio... To increase the robustness of the optimization solutions of the mixed-flow pump,the impeller was firstly indirectly parameterized based on the 2D blade design theory.Secondly,the robustness of the optimization solution was mathematically defined,and then calculated by Monte Carlo sampling method.Thirdly,the optimization on the mixed-flow pump′s impeller was decomposed into the optimal and robust sub-optimization problems,to maximize the pump head and efficiency and minimize the fluctuation degree of them under varying working conditions at the same time.Fourthly,using response surface model,a surrogate model was established between the optimization objectives and control variables of the shape of the impeller.Finally,based on a multi-objective genetic optimization algorithm,a two-loop iterative optimization process was designed to find the optimal solution with good robustness.Comparing the original and optimized pump,it is found that the internal flow field of the optimized pump has been improved under various operating conditions,the hydraulic performance has been improved consequently,and the range of high efficient zone has also been widened.Besides,with the changing of working conditions,the change trend of the hydraulic performance of the optimized pump becomes gentler,the flow field distribution is more uniform,and the influence degree of the varia-tion of working conditions decreases,and the operating stability of the pump is improved.It is concluded that the robust optimization method proposed in this paper is a reasonable way to optimize the mixed-flow pump,and provides references for optimization problems of other fluid machinery. 展开更多
关键词 mixed-flow pump multi-objective genetic optimization robust optimization response surface method 2D blade design theory
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基于鲁棒多目标优化方法的UCAV武器投放规划 被引量:3
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作者 谷学强 王楠 +1 位作者 陈璟 沈林成 《系统工程与电子技术》 EI CSCD 北大核心 2013年第4期753-760,共8页
研究了无人作战飞机(unmanned combat aerial vehicles,UCAV)对地攻击阶段的武器投放鲁棒性规划问题。针对现有规划方法在处理战场环境扰动、模型不准确、操作偏差等不确定性因素方面存在的不足,提出了一种鲁棒多目标优化求解策略。首先... 研究了无人作战飞机(unmanned combat aerial vehicles,UCAV)对地攻击阶段的武器投放鲁棒性规划问题。针对现有规划方法在处理战场环境扰动、模型不准确、操作偏差等不确定性因素方面存在的不足,提出了一种鲁棒多目标优化求解策略。首先,建立了飞机机动性能、武器装备性能和战场环境等约束条件模型;其次,使用仿真近似法,建立了优化指标模型,并将武器投放规划问题转化为鲁棒多目标优化问题;然后,设计了一种结合蒙特卡罗方法的快速非支配排序遗传算法对问题进行求解,并采用基于基本轨迹片元的机动轨迹生成策略生成武器投放轨迹。仿真结果表明,该方法能够有效提高武器投放规划的鲁棒性。 展开更多
关键词 飞行器 控制与导航 武器投放规划 鲁棒多目标优化 快速非支配排序遗传算法 基本轨迹片元
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基于改进SOS算法的UCAV鲁棒机动决策研究 被引量:3
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作者 韩瑾 王骁飞 +2 位作者 周虎 孙楚 李聪 《计算机工程与应用》 CSCD 北大核心 2018年第2期168-172,227,共6页
针对无人作战飞机自主空战机动决策问题,提出了一种鲁棒机动决策方法。设计了反映空战态势的鲁棒隶属函数,并基于此设计鲁棒多目标决策函数;针对动作库在机动决策中的不完备性与传统优化方法求解时效性缺陷,运用基于自适应和精英反向学... 针对无人作战飞机自主空战机动决策问题,提出了一种鲁棒机动决策方法。设计了反映空战态势的鲁棒隶属函数,并基于此设计鲁棒多目标决策函数;针对动作库在机动决策中的不完备性与传统优化方法求解时效性缺陷,运用基于自适应和精英反向学习策略改进的共生生物算法,对控制量进行优化进而完成机动决策;仿真结果表明,鲁棒机动决策结果更具优势且改进算法求解具有实时性,满足机动决策需求。 展开更多
关键词 无人作战飞机 自主空战 机动决策 鲁棒多目标优化 共生生物算法
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