Economic ordering decisions with market choice flexibility

Standard approaches to classical inventory control problems treat satisfying a predefined demand level as a constraint. In many practical contexts, however, total demand is comprised of separate demands from different markets or customers. It is not always clear that constraining a producer to satisfy all markets is an optimal approach. Since the inventory‐related cost of an item depends on total demand volume, no clear method exists for determining a market's profitability a priori, based simply on per unit revenue and cost. Moreover, capacity constraints often limit a producer's ability to meet all demands. This paper presents models to address economic ordering decisions when a producer can choose whether to satisfy multiple markets. These models result in a set of nonlinear binary integer programming problems that, in the uncapacitated case, lend themselves to efficient solution due to their special structure. The capacitated versions can be cast as nonlinear knapsack problems, for which we propose a heuristic solution approach that is asymptotically optimal in the number of markets. The models generalize the classical EOQ and EPQ problems and lead to interesting optimization problems with intuitively appealing solution properties and interesting implications for inventory and pricing management. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

Discrete equal‐capacity p‐median problem

This paper examines the discrete equal‐capacity p‐median problem that seeks to locate p new facilities (medians) on a network, each having a given uniform capacity, in order to minimize the sum of distribution costs while satisfying the demand on the network. Such problems arise, for example, in local access and transport area telecommunication network design problems where any number of a set of p facility units can be constructed at the specified candidate sites (hence, the net capacity is an integer multiple of a given unit capacity). We develop various valid inequalities, a separation routine for generating cutting planes that are specific members of such inequalities, as well as an enhanced reformulation that constructs a partial convex hull representation that subsumes an entire class of valid inequalities via its linear programming relaxation. We also propose suitable heuristic schemes for this problem, based on sequentially rounding the continuous relaxation solutions obtained for the various equivalent formulations of the problem. Extensive computational results are provided to demonstrate the effectiveness of the proposed valid inequalities, enhanced formulations, and heuristic schemes. The results indicate that the proposed schemes for tightening the underlying relaxations play a significant role in enhancing the performance of both exact and heuristic solution methods for this class of problems. © 2000 John & Sons, Inc. Naval Research Logistics 47: 166–183, 2000.     

高炮群火力优化分配的指派模型

火力优化分配是高炮群指挥控制的关键环节。依据有严格理论证明和实用价值的指派问题及其解法(匈牙利法),构建了一对一射击和多对一射击情形下的高炮群火力优化分配的指派模型,探讨了该模型的求解,分析了该模型的实际应用,并通过具体实例对该模型进行了初步验证。该模型的解法被证明是多项式时间算法,满足作战实时性要求。实际应用表明该模型用于解决高炮群的火力分配问题是有效的。     

Mathematical formulation and heuristic algorithm for the block relocation and loading problem

This study considers the block relocation and loading problem in container terminals. The optimal loading sequence and relocation location are simultaneously decided on the basis of the desired ship‐bay and initial yard space configuration. An integer linear programming model is developed to minimize the number of relocations in the yard space on the basis of no shifts in the ship bay. The accuracy of the model is tested on small‐scale scenarios by using CPLEX. Considering the problem size in the real world, we present a rule‐based heuristic method that is combined with a mathematical model for the removal, loading, and relocation operations. The influence of rules on algorithm performance is also analyzed, and the heuristic algorithm is compared with different types of algorithms in the literature. The extensive numerical experiments show the efficiency of the proposed heuristic algorithm.     

话务女兵业务训练周期的心理特点

针对空军某基地通信站女兵连话务女兵的业务训练周期逐渐变长的情况进行研究,将话务专业的"训练周期"划分为基础业务训练阶段、上机跟班训练阶段、考核冲刺阶段、单放后适应阶段及业务熟练阶段5个阶段。从心理学的角度入手进行原因及对策分析,建立"兴奋期-适应期-疲劳期-调整期-实现期"的心理周期模型。以此为框架分析女新兵在各个训练阶段的心理特点,分别以"培养和提高自信""注意集中和正确归因""焦虑情绪和心境状态的调节"及"目标设置"为重点制定阶段性对策,并着眼训练全过程,从帮助新兵持续保持适当的动机水平的角度提出应对办法。     

功能性军事体能训练与心理训练结合运用探索——以新兵体能训练为例

在军队改革的大环境下,军事训练从难从严向实战化聚焦将成为日常训练的常态,而体能训练就是其中最为基础和重要的训练。但是,现阶段的军事体能训练仍然存在着训练理论不系统、训练方法不科学、相关心理指导和心理训练缺乏等弱点,从而造成体能训练成绩提升缓慢、训练损伤居高不下的问题。本文运用功能性军事体能训练和心理训练相结合的方法,从新兵体能训练着手,对其进行身心干预,旨在增强心理适应能力、提高训练成绩、减少训练损伤,为提高部队实战化训练水平打下基础。     

匈牙利算法在多目标分配中的应用

在多目标攻击决策中 ,根据 Harold提出的目标优势函数 ,分析了使所有目标机的总优势函数为指派问题 ,运用匈牙利算法对 n对 n的最优目标分配指派问题进行求解 ,并把它推广至 n对 m的多目标分配中。仿真结果表明匈牙利算法对于此类多目标分配指派问题的求解是十分有效的。     

火灾统计失实问题的现状及对策

以四川省为例介绍火灾统计失实的情况 ,并分析火灾统计失实问题的原因 ,提出纠正火灾统计失实问题的工作意见。     

四川省消防部队基层官兵心理问题调研及分析

为了掌握四川省公安消防部队基层官兵的心理健康状况 ,找准发生引起心理问题和不健康因素的应激源及其特点 ,我们对消防部队基层官兵进行了心理问题调研 ,发现公安消防部队基层官兵中存在不同比例的各种心理问题。他们心理负荷较重 ,紧张性生活事件经历的特点与一般人群不完全一样。为此 ,应在部队的经常性思想工作中引进和建立适合消防部队特点的心理教育疏导工作机制 ,有针对性地采取有效措施预防和减少消防部队官兵心理障碍的发生 ,确保部队的高度稳定和保持昂扬的斗志 ,完成各项任务     

大学生的心理特点与创新潜力的挖掘

当代大学生在社会认知、社会情感、意志品质等心理因素上存在着这一阶段的普遍特点 ,这些特点为挖掘大学生的创造潜能提供了得天独厚的条件 ,高校应抓住这些特点有的放矢地对学生进行创新引导