基于神经网络和遗传算法的锭子弹性管性能优化

为得到减振弹性管对下锭胆的支承弹性和锭子高速运动下的稳定性等性能的最优匹配效率,依据减振弹性管的等效抗弯刚度及底部等效刚度系数公式,利用MatLab数值分析软件构建弹性管抗弯刚度和底部挠度数学模型。首先,结合Isight优化软件基于径向基神经网络构建其近似模型,且使精度达到可接受水平,并以模型的关键结构参数弹性模量、螺距、槽宽、壁厚为设计变量,结合遗传算法对弹性管抗弯刚度和底部挠度进行多目标优化设计,得到Pareto最优解集和Pareto前沿图,确定出减振弹性管结构工艺参数的优化方案。通过对优化数据进行分析发现,该方案在保证减振弹性管弹性的同时,其底部振幅明显减弱。     

开关磁阻电机结构性转矩脉动抑制方法

开关磁阻电机具有结构简单、成本低和调速范围广等优势,但其双凸极结构和控制器的开关特性,导致存在转矩脉动现象,使得抑制转矩脉动成为焦点问题。首先从开关磁阻电机的结构和运行机理出发,针对线性解析方法难以分析转矩特征的问题,建立电机有限元模型求解出转矩特征并进行样机验证试验。分析样机结构参数对转矩脉动的影响,针对结构参数耦合问题,选择NSGA-Ⅱ算法在参数优化平台上对样机结构参数进行多目标寻优,在保证优化后样机的转矩脉动系数和平均转矩均优于初始电机的条件下,最终获得样机最优化结果。结果表明,不同结构参数对电机转矩的影响有较大的差异,对结构参数的优化能有效地抑制转矩脉动,该参数优化方法可以为开关磁阻电机结构性转矩脉动抑制提供参考。     

A knowledge-based archive multi-objective simulated annealing algorithm to optimize series–parallel system with choice of redundancy strategies

Redundancy allocation problem (RAP) is one of the best-developed problems in reliability engineering studies. This problem follows to optimize the reliability of a system containing s sub-systems under different constraints, including cost, weight, and volume restrictions using redundant components for each sub-system. Various solving methodologies have been used to optimize this problem, including exact, heuristic, and meta-heuristic algorithms. In this paper, an efficient multi-objective meta-heuristic algorithm based on simulated annealing (SA) is developed to solve multi-objective RAP (MORAP). This algorithm is knowledge-based archive multi-objective simulated annealing (KBAMOSA). KBAMOSA applies a memory matrix to reinforce the neighborhood structure to achieve better quality solutions. The results analysis and comparisons demonstrate the performance of the proposed algorithm for solving MORAP.     

SDN中基于KMOBPSO的高可靠性控制器部署算法

针对SDN中控制器系统的单节点故障问题,兼顾系统成本和系统时延,应用N+1冗余备份模型来提高SDN控制器部署的可靠性,并将其抽象为多目标优化问题.同时,提出了一种融合K-means聚类算法和遗传算子的多目标二进制粒子群算法——KMOBPSO算法,以求解SDN控制器高可靠性部署问题的解.仿真结果表明,所提算法具有求解精度高、分布均匀、沿Pareto前沿面覆盖广的特点,能够显著提高SDN中控制器部署的可靠性.     

Multi-objective particle swarm optimisation based integrated production inventory routing planning for efficient perishable food logistics operations

Sustainable and efficient food supply chain has become an essential component of one’s life. The model proposed in this paper is deeply linked to people's quality of life as a result of which there is a large incentive to fulfil customer demands through it. This proposed model can enhance food quality by making the best possible food quality accessible to customers, construct a sustainable logistics system considering its environmental impact and ensure the customer demand to be fulfilled as fast as possible. In this paper, an extended model is examined that builds a unified planning problem for efficient food logistics operations where four important objectives are viewed: minimising the total expense of the system, maximising the average food quality along with the minimisation of the amount of CO₂ emissions in transportation along with production and total weighted delivery lead time minimisation. A four objective mixed integer linear programming model for intelligent food logistics system is developed in the paper. The optimisation of the formulated mathematical model is proposed using a modified multi-objective particle swarm optimisation algorithm with multiple social structures: MO-GLNPSO (Multi-Objective Global Local Near-Neighbour Particle Swarm Optimisation). Computational results of a case study on a given dataset as well as on multiple small, medium and large-scale datasets followed by sensitivity analysis show the potency and effectiveness of the introduced method. Lastly, there has been a scope for future study displayed which would lead to the further progress of these types of models.     

NSGA-Ⅱ和NSGA-Ⅲ应用于换热网络多目标优化的对比

针对换热网络多目标优化问题，采用目前应用较广泛的两种多目标遗传算法，即NSGA-Ⅱ和NSGA-Ⅲ，对两种算法的性能进行对比研究。案例研究结果表明，NSGA-Ⅱ算法比NSGA-Ⅲ算法运行效率更高，NSGA-Ⅲ的运行时间是NSGA-Ⅱ的2倍以上；NSGA-Ⅱ算法的应用并不严格地受限于3个目标的最大目标数量，NSGA-Ⅱ在求解大于3个目标的多目标优化问题时也可能具有良好的性能，目标数量并非选择NSGA-Ⅱ和NSGA-Ⅲ算法的严格标准。对10×5换热网络案例进行4个相关目标改造优化时，从换热网络的单一性能指标来看，NSGA-Ⅱ算法更容易获得各目标的极值。从最小年度总费用的评价指标来看，两种算法的最优方案效果相近。对7×3换热网络案例进行6个目标的优化时，NSGA-Ⅲ算法得到各目标的极值较优。从最小年度总费用的评价指标来看，NSGA-Ⅲ算法获得的投资费用和年度总费用更小。对于目标函数数量不超过3个，或者3个以上具有一定相关性的多目标优化问题，推荐优先使用NSGA-Ⅱ算法实现快速寻优；而NSGA-Ⅲ算法由于其基于参考点的选择机制，运行效率较慢，更适合用于收敛困难的高维多目标优化问题。     

随车起重机伸缩臂截面多目标优化

为了提高某火箭炮弹药装填车随车起重机伸缩臂的结构刚度,减轻结构质量,建立了随车起重机伸缩臂参数化模型,并对伸缩臂在水平受载状态下进行仿真分析。以伸缩臂截面尺寸参数为设计变量,借助最优拉丁超立方试验设计建立样本空间,构造响应面多项式函数近似模型。在此基础上,利用NSGA-Ⅱ型遗传算法对伸缩臂自身重量、挠度进行多目标优化。优化结果表明:伸缩臂质量减轻了24.5%,减重效果明显。文中所采用的将参数化建模、有限元分析和数值寻优相结合的优化方法,可为起重机伸缩臂截面优化提供一定的参考。     

基于改进人工蜂群算法的多目标绿色柔性作业车间调度研究

针对多目标绿色柔性作业车间调度问题（MGFJSP）的特点，提出从碳排放量、噪声和废弃物这3个指标来综合评定环境污染程度，建立了以最小化最大完成时间和环境污染程度为优化目标的MGFJSP模型，并提出了一种改进的人工蜂群算法来求解该模型。算法的具体改进包括：设计了一种三维向量的编码和对应解码方案，在跟随蜂搜索阶段引入一种有效的动态邻域搜索操作来提高算法的局部搜索能力，在侦查蜂阶段提出产生新食物源的策略用于增加种群的多样性。最后进行了实验研究与算法对比，以验证所建模型和所提算法的有效性。     

城市规划中的水资源承载力计算——以惠州市为例

探讨水资源承载力综合评估和多目标计算理论在城市规划中的应用。运用灰色多层次综合评估模型对惠州市水资源承载力进行定性的综合评价,应用多目标规划理论对城市经济发展规划不同方案下的惠州市水资源承载力作了定量计算。     

安徽省水资源宏观经济优化模型研究

以水资源可持续发展为出发点,探讨了一种可以同时兼顾经济发展、水资源利用和社会效益的多目标水资源宏观经济模型的建立方法,通过引入带权2-模评价函数,将多目标优化问题转变成单目标优化问题。以2002年为现状水平年,对安徽省2010年的产业结构及产业规模进行优化分析。结果表明,多目标模型求得的总用水量较单目标模型明显降低,而两模型优化的产业规模与结构差别不大,体现了高用水效率行业优先发展的要求。