Optimal joint preventive maintenance and production policies

We study joint preventive maintenance (PM) and production policies for an unreliable production‐inventory system in which maintenance/repair times are non‐negligible and stochastic. A joint policy decides (a) whether or not to perform PM and (b) if PM is not performed, then how much to produce. We consider a discrete‐time system, formulating the problem as a Markov decision process (MDP) model. The focus of the work is on the structural properties of optimal joint policies, given the system state comprised of the system's age and the inventory level. Although our analysis indicates that the structure of optimal joint policies is very complex in general, we are able to characterize several properties regarding PM and production, including optimal production/maintenance actions under backlogging and high inventory levels, and conditions under which the PM portion of the joint policy has a control‐limit structure. In further special cases, such as when PM set‐up costs are negligible compared to PM times, we are able to establish some additional structural properties. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.     

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.     

基于分层结构的故障诊断专家系统RDSC方案

针对军事指挥自动化系统中的硬件设备,运用分层结构专家系统技术实现对系统的远程故障诊断与维护支持,提出了远程维护和故障修复支持技术模型,并对该模型的专家系统技术进行探讨,给出了基于CLIPS专家系统的一个实现模型,最后阐述了专家系统中推理机与知识库的设计和实现.     

Optimal production ramp-up in the smartphone manufacturing industry

Motivated by challenges in the smartphone manufacturing industry, we develop a dynamic production ramp-up model that can be applied to economically satisfy nonstationary demand for short-life-cycle products by high-tech companies. Due to shorter life cycles and more rapid evolution of smartphones, production ramp-up has been increasingly critical to the success of a new smartphone. In the production ramp-up, the key challenge is to match the increasing capacity to nonstationary demand. The high-tech smartphone manufacturers are urged to jointly consider the effect of increasing capacity and decreasing demand. We study the production planning problem using a high-dimensional Markov decision process (MDP) model to characterize the production ramp-up. To address the curse of dimensionality, we refine Monte Carlo tree search (MCTS) algorithm and theoretically analyze its convergence and computational complexity. In a real case study, we find that the MDP model achieves revenue improvement by stopping producing the existing product earlier than the benchmark policy. In synthetic instances, we validate that the proposed MCTS algorithm saves computation time without loss of solution quality compared with traditional value iteration algorithm. As part of the Lenovo production solution, our MDP model enables high-tech smartphone manufacturers to better plan the production ramp-up.     

陕西文学旅游资源的开发生产与营销策划

陕西具有丰富的文学旅游资源,这些资源具有广阔的开发和利用空间。文章就陕西文学旅游资源开发现状进行分析,针对目前存在的问题提出开发生产和营销策略,即要处理好旅游主体、旅游客体和旅游媒体三者的关系,促进陕西旅游可持续发展。     

亚细亚生产方式研究概况及其意义

马克思在研究亚洲或东方社会的状况时,提到亚细亚生产方式的概念,对此概念的严格定义则不是马克思关注的焦点,他的关注点集中在东西生产方式的区别上,以及当时东方社会为何遭受到西方社会的打击,并在此基础上为包括东方国家在内的落后国家寻找一条出路。然而,后人却对亚细亚生产方式概念进行了各种各样的论争,这虽有时代背景上的原因,也有诸多理论上的原因,无疑也背离了马克思探讨亚细亚生产方式的原意。可是另一方面,通过对亚细亚生产方式的研究和争论,有助于了解包括中国在内的亚洲国家的历史和现状。了解自身历史的生产方式,以及和西欧生产方式进行对比,对于现代化进程中的中国有着很大的借鉴和启发意义。     

谈英语教学中学生创造思维的培养

目前,我国外语教学普遍存在费时较多、收效较低的现象,特别是精读课教学,向来只注重给学生注入语言知识,而轻视学生创造思维能力的培养。要解决这一问题,外语教学工作者必须改变教学观念,避免在外语课教学中只重识记而轻思维这一现象。     

基于规则预置的应急事件指挥控制建模研究

为提高应急事件仿真过程中指挥控制模型的智能化程度和仿真结果的可信度,分析了应急事件指挥实体的指挥控制过程和指挥实体阃的信息交互关系,建立了基于预置规则的指挥控制模型,提出了驱动指挥控制模型运转的、表达应急事件指挥专业化知识的产生式指挥控制规则表达方式,重点研究了指挥控制规则的分类、定义和设计方法,并对该方法在仿真系统中的应用进行了分析,取得了比较理想的模拟效果.     

Capacity expansion and cost efficiency improvement in the warehouse problem

The warehouse problem with deterministic production cost, selling prices, and demand was introduced in the 1950s and there is a renewed interest recently due to its applications in energy storage and arbitrage. In this paper, we consider two extensions of the warehouse problem and develop efficient computational algorithms for finding their optimal solutions. First, we consider a model where the firm can invest in capacity expansion projects for the warehouse while simultaneously making production and sales decisions in each period. We show that this problem can be solved with a computational complexity that is linear in the product of the length of the planning horizon and the number of capacity expansion projects. We then consider a problem in which the firm can invest to improve production cost efficiency while simultaneously making production and sales decisions in each period. The resulting optimization problem is non‐convex with integer decision variables. We show that, under some mild conditions on the cost data, the problem can be solved in linear computational time. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 367–373, 2016     

Multiple common due dates

Common due date problems have been extensively discussed in the scheduling literature. Initially, these problems discussed finding a common due date for a set of jobs on a single machine. These single machine problems were later extended to finding the common due date on a set of parallel machines. This paper further extends the single machine problem to finding multiple common due dates on a single machine. For a basic and important class of penalty functions, we show that this problem is comparable to the parallel machine problem. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 293–298, 2001