基于遗传算法优化网络权值的装箱问题研究

通过对Hopfield网络模型的研究，把一种类型的装箱问题转化成Hopfield网络模型，再利用遗传算法优化Hopfield网络中的连接权值，形成混合优化算法求解装箱问题，最后通过实例验证了该算法的有效性。     

虚拟PDM环境下基于特征增长的协同设计

协同设计目前已经成为解决复杂产品设计问题的关键技术之一.在分析了现有协同设计问题的基础上,提出通过构建虚拟PDM(VPDM,Virtual PDM),应用交换特征增长数据的方法,来解决企业间异构PDM、CAD应用系统的协同设计问题.给出了虚拟PDM的定义,并介绍了基于虚拟PDM进行协同设计的基本原理.建立了基于虚拟PD...     

商贸城消防安全管理存在问题及对策

针对贵州省商贸城商业用房的消防安全管理工作现状的分析,提出以＂防火墙＂工作建设为契机,加大对商贸城商业用房的消防安全管理力度,使此项重而难的工作逐步走向良好轨道,避免出现重大火灾事故,为构建和谐社会奠定良好基础。     

Bounded flexibility in days‐on and days‐off scheduling

This article presents a flexible days‐on and days‐off scheduling problem and develops an exact branch and price (B&P) algorithm to find solutions. The main objective is to minimize the size of the total workforce required to cover time‐varying demand over a planning horizon that may extend up to 12 weeks. A new aspect of the problem is the general restriction that the number of consecutive days on and the number of consecutive days off must each fall within a predefined range. Moreover, the total assignment of working days in the planning horizon cannot exceed some maximum value. In the B&P framework, the master problem is stated as a set covering‐type problem whose columns are generated iteratively by solving one of three different subproblems. The first is an implicit model, the second is a resource constrained shortest path problem, and the third is a dynamic program. Computational experiments using both real‐word and randomly generated data show that workforce reductions up to 66% are possible with highly flexible days‐on and days‐off patterns. When evaluating the performance of the three subproblems, it was found that each yielded equivalent solutions but the dynamic program proved to be significantly more efficient. © 2013 Wiley Periodicals, Inc. Naval Research Logistics 60: 678–701, 2013     

The knapsack problem with a minimum filling constraint

We study a knapsack problem with an additional minimum filling constraint, such that the total weight of selected items cannot be less than a given threshold. The problem has several applications in shipping, e‐commerce, and transportation service procurement. When the threshold equals the knapsack capacity, even finding a feasible solution to the problem is NP‐hard. Therefore, we consider the case when the ratio α of threshold to capacity is less than 1. For this case, we develop an approximation scheme that returns a feasible solution with a total profit not less than (1 ‐ ε) times the total profit of an optimal solution for any ε > 0, and with a running time polynomial in the number of items, 1/ε, and 1/(1‐α). © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

需求可拆分的应急物资调度问题的蚁群算法

应急物资调度问题是个典型的需求可拆分的车辆路径问题,区别于传统的车辆路径问题,将每个需求节点只能由一辆车访问的约束去除,允许需求节点由多辆车进行访问。针对应急物资调度问题的特点,建立相应的多目标车辆路径数学规划模型(SDVRP),并根据模型特点设计改进蚁群优化算法。最后,进行相应的算例分析,验证了该模型和算法的有效性。     

瓶颈指派问题的一种多项式时间算法

本文对瓶颈指派问题给出了一种新的算法,该算法不需要利用最大流算法,而类似于解经典指派问题的匈牙利算法。该算法是一个多项式时间算法,其复杂性为Ｏ（ｎ３）     

Screening multi-dimensional heterogeneous populations for infectious diseases under scarce testing resources,with application to COVID-19

Testing provides essential information for managing infectious disease outbreaks, such as the COVID-19 pandemic. When testing resources are scarce, an important managerial decision is who to test. This decision is compounded by the fact that potential testing subjects are heterogeneous in multiple dimensions that are important to consider, including their likelihood of being disease-positive, and how much potential harm would be averted through testing and the subsequent interventions. To increase testing coverage, pooled testing can be utilized, but this comes at a cost of increased false-negatives when the test is imperfect. Then, the decision problem is to partition the heterogeneous testing population into three mutually exclusive sets: those to be individually tested, those to be pool tested, and those not to be tested. Additionally, the subjects to be pool tested must be further partitioned into testing pools, potentially containing different numbers of subjects. The objectives include the minimization of harm (through detection and mitigation) or maximization of testing coverage. We develop data-driven optimization models and algorithms to design pooled testing strategies, and show, via a COVID-19 contact tracing case study, that the proposed testing strategies can substantially outperform the current practice used for COVID-19 contact tracing (individually testing those contacts with symptoms). Our results demonstrate the substantial benefits of optimizing the testing design, while considering the multiple dimensions of population heterogeneity and the limited testing capacity.     

无线网络控制系统一致性研究

通过构建李雅普诺夫函数,对具有不同拓扑结构的无线网络控制系统的一致性问题进行了研究。利用网络结构的邻接矩阵对网络拓扑结构进行描述,同时构造系统的延迟矩阵,结合复杂网络理论中的聚类系数、耦合强度的概念,对系统进行建模。针对复杂网络中常用的两种结构,构建不同的邻接矩阵和延迟矩阵,利用线性矩阵不等式的方法,给出使系统稳定的一般性条件。最后仿真结果验证了方法的有效性。     

关于《消防法》实施以来的几点思考

2009年《消防法》实施以来,消防工作得到了长足的发展,但也反映出一定的问题。分析了《消防法》实施几年来在执法主体力量、概念界定、法律术语等方面中存在的问题,认为应通过合理考虑执法力量状况、理性看待法律条文本身、主动形成执法合作意识等措施,更好地发挥《消防法》在消防监督管理中的重要作用。