改进粒子群算法及其对热连轧机负荷分配优化的研究

提出一种基于适应度方差的权重梯度方向变异的改进粒子群优化算法（IPSO）,通过判断适应度方差,按照权重梯度方向进行变异操作,解决了PSO算法的早熟收敛和易于陷入局部极值的问题.应用IPSO算法对精轧机组负荷分配进行优化,根据负荷分配优化策略,给出综合板形板厚的最小方差目标函数,在实现各机架负荷分配优化的同时,提高板形质量.仿真结果表明,该算法计算精度高,收敛速度快,为精轧机组轧制规程的智能优化设计提供了一种新的有效方法.  

基于混合蚂蚁算法的物流配送路径优化问题研究

论文针对物流配送路径优化问题,提出了一种混合蚂蚁算法,以克服单用蚂蚁算法求解问题时间复杂度过大的难点,论文还研究了该算法解的二次优化方法以更适合实际需要。实验表明该算法运行效果好。  

Computer aided reliability for optimum maintenance planning

Computer aided Maintenance planning for mechanical equipment is presented in this work to implement the optimized extensive maintenance plan at a specific time horizon. The objective is to interchange the unscheduled corrective maintenance into scheduled preventive maintenance depending on historical data of equipment. This work is concerned with development of reliability analysis based on Weibull distribution. An optimization technique has been developed to provide the optimized preventive maintenance plan for the whole equipment during a required time horizon.  

一种基于遗传算法的无线传感器网络节点优化方法

针对基于无线传感器网络的测控系统的特殊性,提出了在满足测控节点连通约束条件下使节点数量最少的模型,并采用遗传算法进行优化计算.为了提高节点多时的收敛速度,提出了基于二分法的遗传算法,结果表明该算法可以大大减少染色体长度.提高优化收敛速度,最后给出了实例.  

基于Web GIS的物流电子商务与配送网络优化集成

Web GIS是一种基于Internet技术的地理信息系统，既满足了业务流程的需要，又使已有的资源在最大范围内得到共享。本文简单介绍了Web GIS的原理和特点，结合实例着重阐述了应用该技术建立应用系统的方法，并讨论了如何在MapXtreme平台上开发和建立物流配送流程自动化系统与配送优化功能的集成。  

基于免疫算法的车辆路径优化问题

分析了车辆路径问题的研究方法和免疫算法相对于其它进化算法的优势,提出了用免疫算法求解车辆路径问题的方法。在算法的求解过程中,构造了一种新的编码方式,在减少编码长度的基础上能够提高算法的运行效率。通过免疫记忆库的设计以及抗体之间浓度的促进和抑制机制,本算法可以实现解的多样性,避免收敛于局部最优解,同时可以有效地防止在进化的过程中失去最优解的可能性。实验结果表明,本算法可以快速求得优化解,是求解车辆路径问题的一种有效算法。  

机械结构多机分布式优化的集成策略研究

为了解决复杂机械结构的优化集成问题，提出了跨广义优化平台与有限元分析平台的多计算机分布式优化的集成策略及系统总体框架，详细探讨了实现集成的一些关键技术，包括在有限元前处理中的边界载荷条件的自动施加、网格自动修改、数据通讯问题、远程控制技术等，提出了相应的解决方案，并已有效地用于求解液压挖掘机的广义优化模型。  

Sensor Distribution Optimization Based on Extending-tree in Sensor Network

In a sensor network,reasonable distribution of sensor nodes will do much good to the improvement of sensorial ability.In a sensor network constructed by randomly scattering,a better sensing coverage can be achieved by topology adjustment utilizing mobility of some sensor nodes.To solve this problem,we define an extending-tree in the sensor network using Voronoi diagrams and Delaunay network.On this base,a new optimization algorithm of sensor node distribution based on genetic algorithm is designed,which provides a sound effective means to improve the sensorial ability of network.Simulation output shows that this algorithm can achieve an optimizing node distribution in the object area,by which sensorial ability of the whole sensor network can be improved at a relatively low cost.  

多物流中心协同配送车辆调度模型研究

提出了基于多Agent的物流中心协同配送车辆配载调度系统框架。系统中的Agent以自组织方式暂时结盟，结盟原则是联盟内成员完成物流任务成本最小。重点研究了联盟成员实施协同配送车辆配载调度优化算法以及结合配送货物共有性、车辆负载及行驶路径的基因自适应换位算子，并就实施协同配送利益分享协商模型中的协商协议、协商策略进行重点分析。实验结果表明，自组织协同配送可以降低成本，提高物流配送效益。  

A classification of methods for distributed system optimization based on formulation structure

Augmented Lagrangian coordination (ALC) is a provably convergent coordination method for multidisciplinary design optimization (MDO) that is able to treat both linking variables and linking functions (i.e. system-wide objectives and constraints). Contrary to quasi-separable problems with only linking variables, the presence of linking functions may hinder the parallel solution of subproblems and the use of the efficient alternating directions method of multipliers. We show that this unfortunate situation is not the case for MDO problems with block-separable linking constraints. We derive a centralized formulation of ALC for block-separable constraints, which does allow parallel solution of subproblems. Similarly, we derive a distributed coordination variant for which subproblems cannot be solved in parallel, but that still enables the use of the alternating direction method of multipliers. The approach can also be used for other existing MDO coordination strategies such that they can include block-separable linking constraints. This work is funded by MicroNed, grant number 10005898.