联合作战军民融合问题研究

文章研究联合作战军民融合问题,提出不断深化联合作战军民融合思想意识,构建完善联合作战军民融合体制机制,加强联合作战军民融合的平时准备。     

一体化联合作战精确控制问题

文中主要对一体化联合作战中的精确控制内涵进行了阐述,然后分别从重要性和实现途径两个方面对作战时序的精确控制、作战空间的精确控制、作战目标的精确控制和作战信息环境的精确控制进行探讨。     

陆军部队进攻战斗效果评估模型

战斗效果评估是部队指挥员进行作战决策的重要依据。以信息化条件下贯彻体系破击战思想为指导,把陆军部队进攻战斗程序作为研究对象,借鉴美军的“三段式”作战效果评估方法和网络中心战有关理论,构建了陆军部队进攻战斗效果评估“三级、四段”式的方法步骤、“四段”式效果评估指标体系和效果评估数学模型,为指挥员通过效果评估科学决策如何贯彻体系破击战思想提供参考。     

Route optimization for multiple searchers

We consider a discrete time‐and‐space route‐optimization problem across a finite time horizon in which multiple searchers seek to detect one or more probabilistically moving targets. This article formulates a novel convex mixed‐integer nonlinear program for this problem that generalizes earlier models to situations with multiple targets, searcher deconfliction, and target‐ and location‐dependent search effectiveness. We present two solution approaches, one based on the cutting‐plane method and the other on linearization. These approaches result in the first practical exact algorithms for solving this important problem, which arises broadly in military, rescue, law enforcement, and border patrol operations. The cutting‐plane approach solves many realistically sized problem instances in a few minutes, while existing branch‐and‐bound algorithms fail. A specialized cut improves solution time by 50[percnt] in difficult problem instances. The approach based on linearization, which is applicable in important special cases, may further reduce solution time with one or two orders of magnitude. The solution time for the cutting‐plane approach tends to remain constant as the number of searchers grows. In part, then, we overcome the difficulty that earlier solution methods have with many searchers. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

The effects of customer rebates and retailer incentives on a manufacturer's profits and sales

In some industries such as automotive, production costs are largely fixed and therefore maximizing revenue is the main objective. Manufacturers use promotions directed to the end customers and/or retailers in their distribution channels to increase sales and market share. We study a game theoretical model to examine the impact of “retailer incentive” and “customer rebate” promotions on the manufacturer's pricing and the retailer's ordering/sales decisions. The main tradeoff is that customer rebates are given to every customer, while the use of retailer incentives is controlled by the retailer. We consider several models with different demand characteristics and information asymmetry between the manufacturer and a price discriminating retailer, and we determine which promotion would benefit the manufacturer under which market conditions. When demand is deterministic, we find that retailer incentives increase the manufacturer's profits (and sales) while customer rebates do not unless they lead to market expansion. When the uncertainty in demand (“market potential”) is high, a customer rebate can be more profitable than the retailer incentive for the manufacturer. With numerical examples, we provide additional insights on the profit gains by the right choice of promotion.© 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

Terminal allocation problem in a transshipment hub considering bunker consumption

This article investigates the method of allocating arriving vessels to the terminals in transshipment hubs. The terminal allocation decision faced by a shipping alliance has the influence on the scheduled arrival time of vessels and further affects the bunker consumption cost for the vessels. A model is formulated to minimize the bunker consumption cost as well as the transportation cost of inter‐terminal transshipment flows/movements. The capacity limitation of the port resources such as quay cranes (QCs) and berths is taken into account. Besides the terminal allocation, the QC assignment decision is also incorporated in the proposed model. A local branching based method and a particle swarm optimization based method are developed to solve the model in large‐scale problem instances. Numerical experiments are also conducted to validate the effectiveness of the proposed model, which can save around 14% of the cost when compared with the “First Come First Served” decision rule. Moreover, the proposed solution methods not only solve the proposed model within a reasonable computation time, but also obtain near‐optimal results with about 0.1～0.7% relative gap. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 529–548, 2016     

Data-driven research in retail operations—A review

We review the operations research/management science literature on data-driven methods in retail operations. This line of work has grown rapidly in recent years, thanks to the availability of high-quality data, improvements in computing hardware, and parallel developments in machine learning methodologies. We survey state-of-the-art studies in three core aspects of retail operations—assortment optimization, order fulfillment, and inventory management. We then conclude the paper by pointing out some interesting future research possibilities for our community.     

Service design at diagnostic service centers

We study a service design problem in diagnostic service centers, call centers that provide medical advice to patients over the phone about what the appropriate course of action is, based on the caller's symptoms. Due to the tension between increased diagnostic accuracy and the increase in waiting times more in‐depth service requires, managers face a difficult decision in determining the optimal service depth to guide the diagnostic process. The specific problem we consider models the situation when the capacity (staffing level) at the center is fixed, and when the callers have both congestion‐ and noncongestion‐related costs relating to their call. We develop a queueing model incorporating these features and find that the optimal service depth can take one of two different structures, depending on factors such as the nurses' skill level and the maximum potential demand. Sensitivity analyses of the two optimal structures show that they are quite different. In some situations, it may (or may not) be optimal for the manager to try to expand the demand at the center, and increasing skill level may (or may not) increase congestion. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

Double Mover–Stayer model on customer switching in telecommunications industry

Customer acquisition and customer retention are the most important challenges in the increasingly competitive telecommunications industry. Traditional studies of customer switching always assume that customers are homogeneous, and thus that model customer switching behavior follows a Markov formulation. However, this postulation is obviously inappropriate in most instances. Blumen et al. (Cornell Studies of Industrial and Labor Relations, Cornell University Press, Ithaca, NY, 1955) developed the Mover–Stayer (MS) model, a generalization of the Markov chain model, to relax the requirement of homogeneity and allow the presence of heterogeneity with two different types of individuals—“stayers,” who purchase the same kinds of products or services throughout the entire observation period; and “movers,” who look for variety in products or services over time. There are two purpose of this article. First, we extend the MS model to a Double Mover‐Stayer (DMS) model by assuming the existence of three types of individuals in the market: (1) stable and loyal customers, who have stable usage within the same company; (2) instable but loyal customers, whose usage varies within the same company over time; and (3) disloyal customers, who switch from one company to another to seek for new experiences or/and benefits. We also propose an estimation method for the DMS model. Second, we apply the DMS model to telecommunications data and demonstrate how it can be used for pattern identification, hidden knowledge discovery, and decision making. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

陆空火力协同仿真推演验证系统设计

针对陆空联合作战中火力协同方案制订、验证手段方法的不足,采用计算机仿真的方法,从安全防误伤的角度对陆空火力协同方案进行了仿真推演评估。分析了功能需求和体系结构,建立了武器装备运动轨迹模型和陆空火力协同安全性判别模型,研究了仿真时钟推进机制和提高仿真速度的方法,设计了陆空火力协同仿真推演验证系统。作战演习应用表明：该系统仿真推演验证快速、准确、便捷、有效。