城市道路建设时序决策的鲁棒优化

为提高城市道路建设时序决策的鲁棒性,提出了城市道路建设时序决策优化的双 层规划模型。模型假定出行需求在一定范围内扰动,上层规划是在有限资金的约束下寻求各建设阶段的系统总出行时间与系统总出行时间对出行需求的灵敏度之间的综合最小值,下层规划为各建设阶段的随机用户均衡配流。文中推导出了系统总出行时间对出行需求灵敏度的计算式,并给出了模型的求解算法。最后以一个测试路网为例,对基于系统总出行时间、基于灵敏度、基于系统总出行时间与灵敏度综合出行时间的决策优化模型进行了计算分析,结果显示3种决策优化模型均可寻求到各自目标最优的城市道路建设时序,但在需求不确定的情景下基于灵敏度、基于系统总出行时间与灵敏度综合出行时间的决策优化结果更具鲁棒性。     

不确定条件下应急资源布局的鲁棒双层优化模型

针对非常规突发事件中应急资源布局问题,在受灾点需求不确定和应急救援过程分为多个阶段的情景下,建立了省市两级应急储备仓库定位和物资配置的鲁棒双层规划模型。运用相对鲁棒优化方法,将上述具有不确定性系数的双层规划模型转化为从者无关联的确定性线性双层规划,提出了一种混合遗传算法进行求解,实现了省市两级应急资源布局的协同优化。通过实例验证了模型及算法的可行性和有效性。     

鲁棒线性优化问题研究综述

鲁棒优化（ＲＯ）是从计算复杂性的角度研究不确定优化模型鲁棒最优解的数学方法．从单阶段鲁棒优化和多阶段鲁棒优化两个方面对鲁棒线性优化（ＲＬＯ）理论的研究进展进行综述,前者的研究主要基于不同形式的不确定集合,后者的研究则基于前者的方法．研究多阶段不确定决策中决策变量受不确定参数实现值影响的情况,其核心是影响函数连续时的仿射可调鲁棒对应模型和函数离散时的有限适应性模型．最后对ＲＬＯ 的研究前景作了展望．     

基于SUA的鲁棒协同优化方法

首先介绍了多学科环境下不确定性的类型以及各种不确定性发生的阶段和传播方式,并简要描述了多学科系统中不确定性传播方法SUA和近似不确定性传递方法IUP.最后,在此基础上给出了一种鲁棒协同优化的计算框架.     

应急物流车辆调度多目标鲁棒优化研究

针对应急物流车辆调度问题中对于经济性、时效性、可靠性和鲁棒性的多种要求，考虑了含有时间窗、不确定需求、不确定行驶时间，以及路段含有失效风险的多目标鲁棒车辆路径优化问题，通过定义新的成本函数、满意度函数、风险度函数和鲁棒度函数作为四个优化目标来构建模型，并基于鲁棒优化理论将不确定模型转化为确定性鲁棒对应模型求解，为解决不确定环境下优化问题提供了新的思路。算法方面，主要基于SPEA2算法框架求解该多目标模型，针对算法缺陷提出多种改进策略，并通过对比实验证明了改进策略的有效性。     

需求不确定的电动汽车换电站选址鲁棒模型

在电动汽车换电站选址问题中,用户充电需求是重要的输入参数,而需求受到技术发展、电动汽车保有量、国家相关政策等因素的影响,通常较难准确预测。假设交通网络上用户需求是不确定的,利用基约束鲁棒优化方法提出基于用户路径流量不确定的换电站选址鲁棒模型,并将鲁棒模型转换为等价的线性规划。最后应用Nguyen-Dupius网络作为数值算例进行分析,结果表明当解的鲁棒水平较低时,通过适当增加选址成本,可以较大程度地提高解的鲁棒性。同时对模型的重要参数作灵敏性分析,随着鲁棒水平的提高,换电站选址成本对路径流量的波动越来越敏感,续航里程的改变对换电站选址策略影响较大。     

基于鲁棒优化理论的电梯群控调度策略

论文针对不确定线性优化问题,研究其不确定集的选择,初始不确定鲁棒优化模型的建立,以及基于该模型的鲁棒对等式转化问题.然后将鲁棒优化建模方法应用于电梯群控调度问题,建立其鲁棒优化模型,解决了交通流不确定性的影响,从而使调度结果更为合理.结合电梯群控虚拟仿真环境,设计了电梯群控鲁棒优化调度算法,并进行仿真验证.通过与其他调度算法的比较,证明了鲁棒优化调度算法在不同交通流F均具有优良的性能和适应能力.实验表明,鲁棒优化调度方法可以解决交通流预测误差的影响,很好地改善电梯群控调度性能.     

鲁棒稳定界的连续性分析及优化方法

针对一类常见的不确定系统，本文得出了鲁棒稳定界ρ（Ｆ）连续、可微的条件，给出了ρ（Ｆ）对状态反馈Ｆ的微分表达式，以及在极点配置的约束下使ρ（Ｆ）增大的梯度的方法，实例显示，梯度方法非常有效。     

优化H-范数的新技术与鲁棒设计

本文提出了一种全新的Ｈ∞－优化方法：梯度方法。这种优化方法非常灵活，适用范围极广，可用于对系统矩阵中的一般参数进行优化选择，可将Ｈ∞－范数与其它范数加权，构成复合的目标函数，还可处理极点配置等限制条件下的Ｈ∞－优化问题。梯度方法的主要思想就是通过与Ｈ∞－范数直接相关的Ｈａｍｉｌｔｏｎ矩阵定义目标函数ρ（ε，ｐ）具有ｌｉｍρ（ε，ｐ）＝１／‖Ｔ（ｓ，ｐ）‖∞。其中ｐ可为系统矩阵中的任何可变参数。ρ（     

不确定网络结构下的应急物资鲁棒配置模型

灾害发生前的应急物资配置问题具有两个重要的不确定性, 即交通网络中受自然灾害影响而阻断的道路以及受灾点的应急物资需求量. 通过引入两个控制水平参数建立了不确定网络结构下的两阶段应急物资鲁棒配置模型, 并在线性化第2 阶段的回溯问题后提出了求解模型的Benders 分解算法. 数值实验结果表明了所提出的模型的有效性以及所得配置方案的鲁棒性.

     

考虑搬运车辆空载的多行设备布局设计

对于多行设备布局问题,通过对搬运车辆运行情况的分析,建立的模型中以搬运设备的重载运行和空载运行的费用之和最小作为目标函数,设计了相应的遗传算法来求解。通过一个实例进行了模拟计算,进一步与原有模型的仿真结果进行了比较。比较结果说明了利用该模型得到的设备布置方案要优于采用原有模型得到的布置方案。     

A hybrid optimization approach for layout design of unequal-area facilities

A hybrid optimization approach is presented for the layout design of unequal-area facilities. Simulated annealing is used to optimize a randomly generated initial placement on an “extended plane” considering the unequal-area facilities enclosed in magnified envelop blocks. An analytical method is then applied to obtain the optimum placement of each envelop block in the direction of steepest descent. Stepwise reduction of the sizes of the envelop blocks allows controlled convergence in a multi-phase optimization process. The presented test problems include two large size benchmark problems of 50 and 100 facilities of unequal areas. The results indicate that although the computational cost is relatively quite high, the technique is a significant improvement over previously published techniques for unequal-area facilities and can yield solutions of the same quality as obtained by PLANOPT, a general-purpose layout optimization program based on pseudo-exhaustive search.     

Robust hierarchical multiple hypothesis tracker for multiple-object tracking

Multiple object tracking is a fundamental subsystem of many higher level applications such as traffic monitoring, people counting, robotic vision and many more. This paper explains in details the methodology of building a robust hierarchical multiple hypothesis tracker for tracking multiple objects in the videos. The main novelties of our approach are anchor-based track initialization, prediction assistance for unconfirmed track and two virtual measurements for confirmed track. The system is built mainly to deal with the problems of merge, split, fragments and occlusion. The system is divided into two levels where the first level obtains the measurement input from foreground segmentation and clustered optical flow. Only K-best hypothesis and one-to-one association are considered. Two more virtual measurements are constructed to help track retention rate for the second level, which are based on predicted state and division of occluded foreground segments. Track based K-best hypothesis with multiple associations are considered for more comprehensive observation assignment. Histogram intersection testing is performed to limit the tracker bounding box expansion. Simulation results show that all our algorithms perform well in the surroundings mentioned above. Two performance metrics are used; multiple-object tracking accuracy (MOTA) and multiple-object tracking precision (MOTP). Our tracker have performed the best compared to the benchmark trackers in both performance evaluation metrics. The main weakness of our algorithms is the heavy processing requirement.     

Condition based maintenance optimization considering multiple objectives

In condition based maintenance (CBM) optimization, the main optimization objectives include maximizing reliability and minimizing maintenance costs, which are often times conflicting to each other. In this work, we develop a physical programming based approach to deal with the multi-objective condition based maintenance optimization problem. Physical programming presents two major advantages: (1) it is an efficient approach to capture the decision makers’ preferences on the objectives by eliminating the iterative process of adjusting the weights of the objectives, and (2) it is easy to use in that decision makers just need to specify physically meaningful boundaries for the objectives. The maintenance cost and reliability objectives are calculated based on proportional hazards model and a control limit CBM replacement policy. With the proposed approach, the decision maker can systematically and efficiently make good tradeoff between the cost objective and reliability objective. An example is used to illustrate the proposed approach.     

Robust berth scheduling at marine container terminals via hierarchical optimization

In this paper, we present a mathematical model and a solution approach for the discrete berth scheduling problem, where vessel arrival and handling times are not known with certainty. The proposed model provides a robust berth schedule by minimizing the average and the range of the total service times required for serving all vessels at a marine container terminal. Particularly, a bi-objective optimization problem is formulated such that each of the two objective functions contains another optimization problem in its definition. A heuristic algorithm is proposed to solve the resulting robust berth scheduling problem. Simulation is utilized to evaluate the proposed berth scheduling policy as well as to compare it to three vessel service policies usually adopted in practice for scheduling under uncertainty.     

面向受灾差异的跨区域应急救援路径优化

关注各灾区待救人员的不同受伤程度,用“伤员在途可坚持时间”的区别来表征差异化受灾情形,研究带有时间窗限制、基于受灾差异的跨区域应急救援路径优化问题.构建以最小化救援车辆行车总时间为决策目标的车辆路径模型,设计蚁群算法对仿真算例进行求解.讨论考虑受灾差异因素对整个跨区域救援路径优化方案的影响,并对以决策者风险态度为例的关键参数实施敏感性分析.研究结果可为构建高效的应急管理体系提供有益参考.     

Truss optimization considering homologous deformation under multiple loadings

The deformation of a structure shall be called homologous, if a given geometrical relation holds for a given number of structural points before, during, and after the deformation. Some researchers have utilized the idea of structural design with the finite element method. The approaches use the decomposition of the FEM equation or equality equations to obtain homologous deformation. However, weight reduction and response constraints such as stress, displacement or natural frequency cannot be considered by those theories. An optimization method solving the above problems is suggested for obtaining homologous deformation. Homology constraints can be considered under multiple loading conditions as well as a single loading condition. A homology index is defined for multiple loading conditions. Examples are solved to demonstrate the performance of the method.     

Optimal placement of multiple visual sensors considering space coverage and cost constraints

This paper proposes an optimal camera placement method that analyzes static spatial information in various aspects and calculates priorities of spaces using modeling the moving people pattern and simulation of pedestrian movement. To derive characteristics of space and to cover the space efficiently, an agent-based camera placement method has been developed considering the camera performance as well as the space utility extracted from a path finding algorithm. The simulation shows that the method not only determines the optimal number of cameras, but also coordinates the position and orientation of a camera efficiently considering the installation costs. Experimental results show that our approach achieves a great performance enhancement compared to other existing methods.     

Robust optimization with convex model considering bounded constraints on performance variation

In robust optimization, double-looped structures are often adopted where the outer loop is used to seek for the optimal design and the optimization performed in the inner loop is for the robustness assessment of the candidate solutions. However, the double-looped techniques usually will lead to a significant increase in computational efforts. Therefore, in this paper, a new robustness index is developed to handle bounded constraints on performance variation where no optimization run is required for the robustness evaluation work in the inner loop. The computation of this new index is based on the sensitivity Jacobian matrix of the system performances with respect to the uncertainties and it can quantitatively measure the maximal allowable magnitude of system variations. By introducing this index, the robust design problem can be reformulated as a deterministic optimization with robustness indices requirements. Two numerical examples are tested to show the effectiveness and efficiency of the proposed approach, whose solutions and computational efforts are compared to those from a double-looped approach proposed in previous literature.