Deterministic and stochastic scheduling with teamwork tasks

We study a class of new scheduling problems which involve types of teamwork tasks. Each teamwork task consists of several components, and requires a team of processors to complete, with each team member to process a particular component of the task. Once the processor completes its work on the task, it will be available immediately to work on the next task regardless of whether the other components of the last task have been completed or not. Thus, the processors in a team neither have to start, nor have to finish, at the same time as they process a task. A task is completed only when all of its components have been processed. The problem is to find an optimal schedule to process all tasks, under a given objective measure. We consider both deterministic and stochastic models. For the deterministic model, we find that the optimal schedule exhibits the pattern that all processors must adopt the same sequence to process the tasks, even under a general objective function GC = F(f₁(C₁), f₂(C₂), … , f_n(C_n)), where f_i(C_i) is a general, nondecreasing function of the completion time C_i of task i. We show that the optimal sequence to minimize the maximum cost MC = max f_i(C_i) can be derived by a simple rule if there exists an order f₁(t) ≤ … ≤ f_n(t) for all t between the functions {f_i(t)}. We further show that the optimal sequence to minimize the total cost TC = ∑ f_i(C_i) can be constructed by a dynamic programming algorithm. For the stochastic model, we study three optimization criteria: (A) almost sure minimization; (B) stochastic ordering; and (C) expected cost minimization. For criterion (A), we show that the results for the corresponding deterministic model can be easily generalized. However, stochastic problems with criteria (B) and (C) become quite difficult. Conditions under which the optimal solutions can be found for these two criteria are derived. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

Coordinated pricing and inventory control problems with capacity constraints and fixed ordering cost

This article addresses a single‐item, finite‐horizon, periodic‐review coordinated decision model on pricing and inventory control with capacity constraints and fixed ordering cost. Demands in different periods are random and independent of each other, and their distributions depend on the price in the current period. Each period's stochastic demand function is the additive demand model. Pricing and ordering decisions are made at the beginning of each period, and all shortages are backlogged. The objective is to find an optimal policy that maximizes the total expected discounted profit. We show that the profit‐to‐go function is strongly CK‐concave, and the optimal policy has an (s,S,P) ‐like structure. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

舰船成本预测系统中的自变量约简方法

针对舰船成本预测系统中自变量众多且相互关系错综复杂的特点,提出了用模糊粗糙集方法对舰船成本预测系统中的自变量进行约简。在模糊粗糙集方法的框架下,给出了模糊不可分辨关系和相对约简的定义,构建了基于模糊粗糙集的舰船成本预测系统自变量约简模型,并且针对实际的舰船成本预测系统一般是混合数据系统的问题,对广义差别矩阵的定义进行了改进,设计了相应的启发式约简算法。实例分析结果表明:文中所提的方法不仅能使约简的自变量大为减少,而且约简的效果较传统方法更好,且计算过程也更简单。     

效能指数的机载火控雷达研制费用估算模型

为提高机载电子设备研制、生产费用估算的精度,提高估算模型的应用范围和时间跨度,构建了基于效能指数的机载火控雷达研制费用估算模型。在分析机载电子设备研制费用建模特点的基础上,以军用飞机的机载火控雷达设备为研究对象,探讨了其效能指数的构建方法,建立了基于效能指数的研制费用参数模型,并进行实例分析。结果表明,由于效能指数考虑了众多费用驱动因素,该模型形式简明直观,相对误差较小,为研究机载电子设备的费用估算进行了有益的探索。     

加强教育成本核算提高武警院校办学效益

随着社会主义市场经济的不断发展和武警院校管理体制改革的逐步深入,武警院校应加强教育成本核算,立足于现有的经费、资源,精打细算,通过认真的成本核算,优化资源配置,提高办学质量和经费使用效益。     

A misclassification cost‐minimizing evolutionary–neural classification approach

Machine learning algorithms that incorporate misclassification costs have recently received considerable attention. In this paper, we use the principles of evolution to develop and test an evolutionary/genetic algorithm (GA)‐based neural approach that incorporates asymmetric Type I and Type II error costs. Using simulated, real‐world medical and financial data sets, we compare the results of the proposed approach with other statistical, mathematical, and machine learning approaches, which include statistical linear discriminant analysis, back‐propagation artificial neural network, integrated cost preference‐based linear mathematical programming‐based minimize squared deviations, linear integrated cost preference‐based GA, decision trees (C 5.0, and CART), and inexpensive classification with expensive tests algorithm. Our results indicate that the proposed approach incorporating asymmetric error costs results in equal or lower holdout sample misclassification cost when compared with the other statistical, mathematical, and machine learning misclassification cost‐minimizing approaches. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006.     

质量功能展开与多约束条件下的概念设计

针对产品在设计时需要大量的资源,研究了资源的投入影响顾客满意度的问题.提出了质量功能展开与多约束条件相结合进行概念设计的方法.利用质量功能展开的基本原理,通过引进设计属性的实际可达水平和计划可达水平,给出了设计资源约束条件下的优化模型.最后以火控雷达的概念设计为例,以研制费用和研制进度为约束条件建立模型,计算说明此模型是有效的.     

寿命周期费用估算中的敏感度分析

针对寿命周期费用估算和分析时存在的费用不确定性,需要对关键参数进行敏感度分析,否则会影响到结果的正确性.通过分析引起费用不确定性的因素,阐述了敏感度分析的内涵和分析步聚.为了验证该方法,举出示例加以说明.认为:敏感度分析的费用估算与分析中的运用,将对合理决策产生重要作用.     

Graph distance‐dependent labeling related to code assignment in computer networks

For nonnegative integers d₁, d₂, and L(d₁, d₂)‐labeling of a graph G, is a function f : V(G) → {0, 1, 2, …} such that |f(u) − f(v)| ≥ d_i whenever the distance between u and v is i in G, for i = 1, 2. The L(d₁, d₂)‐number of G, λ(G) is the smallest k such that there exists an L(d₁, d₂)‐labeling with the largest label k. These labelings have an application to a computer code assignment problem. The task is to assign integer “control codes” to a network of computer stations with distance restrictions, which allow d₁ ≤ d₂. In this article, we will study the labelings with (d₁, d₂) ∈ {(0, 1), (1, 1), (1, 2)}. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2005     

基于全寿命周期费用分析的可重复使用运载器级数选择

建立了可重复使用运载器全寿命周期费用模型 ,并利用该费用模型分析了不同级数的可重复使用运载器方案的全寿命周期费用 ,对全寿命周期费用的各部分组成比例及其随级数的变化规律进行了分析。研究结果表明两级入轨的可重复使用运载器方案全寿命周期费用最低 ,是基于目前技术水平的一种较优的可重复使用运载器级数选择方案