信息熵与TOPSIS装备保障力量部署方案优化

针对装备保障力量部署方案复杂性和模糊性特点,在分析装备保障力量部署的内容、影响因素及方案优化目的基础上,建立了装备保障力量部署方案评估指标体系,采用信息熵理论来确定评估指标的权重,并提出了基于熵权TOPS IS的装备保障力量部署方案优选方法,使装备保障力量部署方案决策更加科学合理,具有一定的实用性。     

Using stochastic programming to solve an outpatient appointment scheduling problem with random service and arrival times

We study a stochastic outpatient appointment scheduling problem (SOASP) in which we need to design a schedule and an adaptive rescheduling (i.e., resequencing or declining) policy for a set of patients. Each patient has a known type and associated probability distributions of random service duration and random arrival time. Finding a provably optimal solution to this problem requires solving a multistage stochastic mixed‐integer program (MSMIP) with a schedule optimization problem solved at each stage, determining the optimal rescheduling policy over the various random service durations and arrival times. In recognition that this MSMIP is intractable, we first consider a two‐stage model (TSM) that relaxes the nonanticipativity constraints of MSMIP and so yields a lower bound. Second, we derive a set of valid inequalities to strengthen and improve the solvability of the TSM formulation. Third, we obtain an upper bound for the MSMIP by solving the TSM under the feasible (and easily implementable) appointment order (AO) policy, which requires that patients are served in the order of their scheduled appointments, independent of their actual arrival times. Fourth, we propose a Monte Carlo approach to evaluate the relative gap between the MSMIP upper and lower bounds. Finally, in a series of numerical experiments, we show that these two bounds are very close in a wide range of SOASP instances, demonstrating the near‐optimality of the AO policy. We also identify parameter settings that result in a large gap in between these two bounds. Accordingly, we propose an alternative policy based on neighbor‐swapping. We demonstrate that this alternative policy leads to a much tighter upper bound and significantly shrinks the gap.     

某供弹机构现存问题动力学分析及参数优化探讨

介绍了环形杠杆供弹机构的工作原理及其在实际使用中常见的问题,建立了机构的动力学模型,对模型进行动态求解,模拟了机构的工作过程。借助求解结果,针对问题产生的原因进行了动力学分析,在理论上找到了问题产生的根源。在此基础上建立了机构的最优化数学模型,给出了优化方案,最后对优化方案和现有结构进行了比较。     

一类差分方程的三点边值问题的正解

研究了一类离散型三点边值问题:Δ2y(k-1) a(k)f(k,y(k))=0,k∈N={1,2,…,T},Δy(0)=0,y(T 1)=βy(l),式中:f是变号的,l∈N1={2,3,…,T-1},T∈{3,4,…}。应用双锥上的不动点定理,得到了至少存在两个正解的充分条件,并给出了上述边值问题的Green函数。     

Maximizing project cash availability

Consider a project during the life cycle of which there are cash payouts and in‐flows. To better meet his financial commitments, the project owner would like to meet all deadlines without running out of cash. We show that the cash availability objective is similar to the total weighted flowtime used to measure work‐in‐progress performance in the scheduling and inventory control literatures. In this article we provide several specialized solution methods for the problem of minimizing total weighted flowtime in an arbitrary acyclic project network, subject to activity release times and due dates, where the activity weights may be positive or negative and represent cash in‐ and out‐flows. We describe the structure of an optimal solution and provide several efficient algorithms and their complexity based on mincost and maxflow formulations. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

基于接触的捞雷具夹紧爪接触面形状优化

介绍了在捞雷具夹紧爪设计过程中引入的基于接触的有限元形状优化设计方法.传统的机械设计方法仅考虑了零件的几何尺寸,而对其形状的设计却考虑不够,导致设计结果不理想.文中将基于接触的有限元形状优化方法应用于传统的机械设计过程.对捞雷具夹紧爪建立基于有限元分析的优化设计模型,使夹紧爪既能满足打捞鱼雷的要求,又得到了优化的形状.结构的特性与受力状况均得到改善.     

舰艇武器布置问题的一种协同优化算法

针对舰艇武器布置问题的特点,提出了一种基于粒子群优化和分类器系统的协同优化算法,以粒子群优化进行优化计算,用分类器系统消除约束.计算实例表明,该算法能较好地实现优化计算,并能节省大量的计算时间.     

具有热阻、热漏和内不可逆性的联合卡诺热机生态学优化

用有限时间热力学的方法分析具有热阻、热漏、内不可逆性的定常流联合卡诺型热机循环.导出了在傅立叶导热定律下联合循环功率、效率和生态学指标的性能,并进行优化;得到功率、效率和生态学指标之间的优化关系,并由数值计算分析了功率、效率和循环熵产率之间的关系.所得的结果表明,最大生态学指标下的效率十分接近于联合循环可以达到的最大效率;相应的熵产率也要低于以输出功率为优化目标时的熵产率.     

基于蚁群算法的试验流程优化研究

水中兵器的海上试验涉及许多人员、兵力、被试产品、测量设备等,试验周期长、消耗大,因此如何缩短试验周期是亟待研究解决的问题.文中首先将试验流程优化问题转化为车间调度问题,建立了相应的数学模型,再应用蚁群算法转移规则得到中间结果并进行排队以对各种资源约束进行处理.最后将结果利用局部搜索算法优化后作为蚁群算法信息素更新的基础.实例计算结果表明,该方法优化效果良好.     

新型多目标遗传算法及其在导弹射击效能优化中的应用

多目标规划是一类重要的优化模型,有着广泛的实际应用,但其求解至今仍是运筹学的一个难点.针对一般约束多目标优化问题,在设计了新的适应度函数和选择算子的基础上,提出一种新型多目标遗传算法.将其应用于导弹对集群目标射击效能优化问题,验证了算法的有效性.