产品竞争的产业演化模型研究

本文以NW模型为基础,建立了产品竞争的产业演化模型,分析由不同企业组成并有新企业持续随机进入的产业的竞争动态,分析产业内各个企业的投资决策、R＆D策略、技术变化、产品创新以及产业特征的其他方面之间的相互作用。仿真结果表明,该模型很好地再现了生产异质产品的产业的演化过程中呈现出来的典型事实。     

POLICY-COMPARING SIMULATION EXPERIMENTS: DESIGN AND ANALYSIS

One of the principal uses of simulation in business and industry is to compare alternative policies or decision rules for the operation and control of complex systems. The immediate objective of such simulation studies is usually quite simple: to discover the best of the several policies under consideration. The measure of effectiveness used is also usually straightforward, often dollars of cost or profit. The basic experimental design that will produce the best comparison of alternatives is generally agreed upon: all policies should be compared under, to the extent possible, identical experimental conditions, i.e., when randomness is involved, all alternatives in a simulation experiment should be simulated using a common sequence of randomly-generated events.     

通胀周期、金融抑制与企业存货的动态调整

企业存货调整策略的准确识别是有效管理通胀预期的必要条件。本文基于非线性交互效应面板误差纠正模型、从微观层面研究在通胀周期不同阶段,企业存货调整的具体特征。实证结果与反事实对比仿真实验均表明:主导企业存货策略性调整的是通胀预期而不是实际通胀水平。与社会的经验判定不同,企业存货调整对通胀表现出逆周期特征。对大部分行业而言,低通胀阶段,通胀预期的收益效应强于存货调整的成本效应,货币调控无效;高通胀阶段,通胀预期弱化,成本效应凸显,货币调控才有效。两种机制的阈值通胀率约为3.4%,所以,将通胀调控上限定为3.5%符合企业市场行为的特征。各行业存货策略对货币调控、通胀预期的灵敏度有显著差异,房地产、批发零售、机械设备较为敏感,最不敏感的是食品行业。     

碳交易政策下多式联运路径选择问题的鲁棒优化研究

针对碳交易政策下的多式联运路径选择问题,考虑运输时间和单位运费率不确定且其概率分布未知的情况,引入鲁棒优化建模方法对其进行研究。首先利用box不确定集合刻画分布未知的运输时间和运费率,然后在碳交易政策下确定模型的基础上,构建鲁棒性可调节的多式联运路径选择模型,并通过对偶转化得到相对易求解的鲁棒等价模型。实例分析表明,鲁棒模型能较好地处理参数概率分布未知的多式联运路径选择问题,方便决策者根据偏好调整不确定预算水平进行决策。运输时间和单位运费率的不确定性都会影响多式联运路径决策,但是作用机理有所不同。将上述碳交易政策下的模型拓展到其他低碳政策,结果表明多种低碳政策的组合能更好实现多式联运减排。     

Manufacturing strategy: A study of machine tool companies in the UK

This paper describes findings from an empirical study carried out in a group of small to medium sized companies within the U.K. machine tool industry. Notions of manufacturing strategy are discussed and a contingency model of change within production systems is proposed. Based on the model, a research programme is described, the object of which was to determine why firms adopt particular production systems, under what conditions these are changed, and the criteria and procedures which are used. A focus for change is taken to be the make-or-buy decision. The results showed that the key criteria used by the firms in their evaluations were: capacity, utilization and process capability (technology). From the study, it is concluded that response to change was largely based upon operational considerations and that the firms lacked a framework for reviewing the strategic implications of their decisions. Hence, the need is argued for a methodology whereby firms can establish consistent functional strategies, with the plans and policies to achieve them.     

Multi-objectives exception management model for semiconductor back-end environment under turnkey service

On-time delivery is the need for customer satisfaction which is a critical factor in the survival of the semiconductor industry. The on-time-delivery performance of the whole semiconductor turnkey service depends on the performance of the back-end factories. Unfortunately, undesirable and inevitable production variations make it difficult to maintain and improve a factory's performance and more objectives such as cycle time, throughput rate and the due-date accuracy need to be simultaneously considered. This paper presents an exception management model in order to compromise the contradicting needs of delivery accuracy, throughput rate and cycle time. The exception model can be divided into three parts: (1) an integrated performance index is proposed to compromise multiple performance measures; (2) an AWDL (available WIP deviation level) determination model is designed to gather proper AWDLs for triggering exceptions and (3) a WIP correction action is proposed to make abnormal WIP levels back to normal levels as soon as possible. To evaluate the proposed WIP exception management model, a simulation model is constructed and experiments are then conducted. The simulation results show that the proposed model helps back-end factories to set proper exception triggering conditions, reduce uncertainty occurrences and achieve better performances on due dates.     

“政策领域-时间维度”双重视角下新能源汽车产业政策央地协同研究

本文以2009—2018年间中央及地方（以北京市等四个地区为例）颁布的263项新能源汽车产业政策为研究样本,从实施领域角度,将产业政策分为财税支持、行业规范、规划引导、监督保障、其他措施等五类,经政策分解,将政策片段与新能源汽车产业链五个环节进行匹配;在此基础上,测度不同时期产业政策央地总体协同度与政策实施领域间的协同度,并通过逐步回归法,确定影响政策协同的各政策效力指标灵敏度。研究表明："中央-北京"和"中央-深圳"的政策措施协同趋势基本一致,产业价值链各环节发展较均衡,而"中央-上海"和"中央-江苏"的政策措施协同趋势基本一致,存在"重使用、轻研发、轻市场"等失调现象;四地区与中央政策措施的协同差异主要体现在研发、生产和回收环节,提升"政策引导"和"保障措施"指标的政策效力有助于提升央地协同水平。根据政策分析,未来政策制定需从优化中央政策推广方式和加强监管保障等政策措施着手,根据产业链不同环节状况适时调整政策措施。     

房价变动、产业转移与区域协调发展——以京津冀地区为例

构建房价-资本模型，分析房地产行业投资收益对工业再投资的影响，发现：地区间适当的房地产行业投资收益差异有利于工业企业从核心地区向边缘地区转移，差异较大则导致资本流向房价增长过快地区的房地产行业；若地区间房地产行业投资收益差异既定，较大的经济发展差距对产业转移起阻碍作用，激烈的市场竞争则起促进作用。利用京津冀地区13个城市的数据构建面板门限模型，验证了：（1）较低的房价增长率促进了北京市相对低效的资本向外转移，但是北京市与周边地区较大的经济发展差距又阻碍了该趋势。（2）核心区流出的资本优先向次发达地区转移，而落后地区则有被彻底边缘化的风险。为实现京津冀地区协调发展，一方面要加强对京津冀地区房价的宏观调控、防止房价过快增长；另一方面要制定针对边缘地区的优惠政策，引导非首都功能向周边转移。     

基于竞争性信息传播模型的信息失真治理研究

网络谣言是由信息失真产生的不良信息，本文从微博社交网络谣言事件传播演化一般过程出发，研究谣言信息与辟谣信息的竞争传播过程，基于SIR模型进行改进，从系统动力学视角构建谣言信息和辟谣信息的竞争传播模型，并使用Anylogic软件实现模型仿真。实验表明，网民素养较高时，谣言信息的传播规模显著萎缩。节点接触环境中辟谣信息的接触权重较大时，能有效抑制谣言的传播。进而总结了研究的理论意义和实践意义，提出了提高网民素质、对网络节点的接触环境进行调控等网络空间不良信息治理建议。     

Development and analysis of mathematical and simulation models of decision-making tools for remanufacturing

This article presents decision-making tools for remanufacturing. The first decision-making tool was used to address inventory lot-sizing problems in a hybrid remanufacturing–manufacturing system with varying remanufacturing fraction. In this article, the new inventory lot-sizing model with variable remanufacturing lot sizes has been shown to exhibit better performance than the benchmark model with fixed remanufacturing lot sizes. The new inventory lot-sizing model is anticipated to become a valuable decision-making tool in companies that are planning to adopt remanufacturing. The second decision-making tool was applied to address a production and inventory planning problem in a remanufacturing system considering different remanufacturing policies for a given remanufacturing strategy. For a remanufacture-to-stock system with two quality remanufacturables groups four alternative policies were examined, a policy which specifies simultaneous processing utilising dedicated resources was shown to be the best policy to achieve a shorter remanufacturing cycle time. For a remanufacture-to-order system with two quality remanufacturables groups, the three relevant policies of the four alternative policies were examined, a policy which specifies sequential processing and switching between various quality remanufacturables groups was shown to be the best policy to achieve a shorter remanufacturing cycle time. The production and inventory planning simulation models in a remanufacturing system are expected to become significant decision-making tools in remanufacturing operations.     

Key issues in managing information

In this article data, information and state of knowledge are described and then related to the decision-making process. The theme that data is a valuable commodity needing management is then developed. Then follows a section on computers, organizational policies and central and distributed processing. Some contractual aspects relating to procurement are described. Examples are given of actual applications in British industry, followed by discussion of two different issues, namely privacy and computer crime. The author draws the conclusion that ‘information’ per se is a personal, corporate and management asset which needs proper understanding and management in the computer era.     

A Study of Labor Allocation Strategies in Cellular Manufacturing

Current research studies in cellular manufacturing have considered environments constrained only by the machine resource, when in fact the flexibility of manufacturing cells is derived mainly from its allocation of the labor resource. This research specifically examines the labor resource in cellular manufacturing, also known as group technology (GT), through a series of simulation experiments on a hypothetical GT shop and recommends conditions under which different labor allocation strategies may be appropriate. The effects of various product routings and scheduling policies on labor allocation are also examined.     

Open Order Rescheduling in Job Shops with Demand Uncertainty: A Simulation Study

This paper addresses the problem of open order rescheduling in a job shop. Results are reported of experiments conducted in a simulation model of an 8-machine job shop. Four different order updating policies are examined. The due-date process is modeled to include several realistic features about the pattern of due-date variability. These features are parameterized and tested at several levels. Tardiness results indicate that open order rescheduling is beneficial only when allowances are loosely set. The results indicate that inventory performance is improved by order rescheduling, particularly in cases when due dates are revised to earlier times than originally forecast.     

Discrete simulation modelling for corporate manpower planning

Manpower planners within South African companies have very few, if any, decision support tools at their disposal to assist them in the formulation of their manpower strategies. Such quantitative tools as do exist are mathematically too sophisticated to be easily understood and implemented by manpower managers who are, on the whole, non numerate. The approach proposed in this paper, namely simulation modelling, discusses and demonstrates a powerful quantitative method which is conceptually easy to understand and whose results are easily interpreted. This particular simulation model examines the impact on organisational staffing levels over time as a result of specific present/proposed manpower policies in the areas of procurement and promotion. Through manipulating the inputs, the manpower planner can, with relative ease, examine the consequences of a range of alternative policies within a very short period of time.     

Passenger and pilot risk minimization in offshore helicopter transportation

In the offshore petroleum industry, employees are transported to and from the offshore installations by helicopter, which represents a major risk. This paper analyzes how to improve transportation safety by solving the helicopter routing problem with a risk objective expressed in terms of expected number of fatalities. A mathematical model is proposed and a tabu search heuristic is applied to this problem. Three routing policies are considered: a direct routing policy, a Hamiltonian routing policy, and a general routing policy. Extensive computational experiments are conducted on instances derived from real data in order to assess and compare these policies under a travel time, a passenger risk and a combined passenger and pilot risk objective. Several management insights can be derived from this study. In particular, our results show that passenger transportation risk can be reduced by increasing travel time at the expense of pilot risk. This can be achieved through a reduction of the average number of passengers onboard by applying either a Hamiltonian or a general routing policy. Our methodology can also be used to derive an equitable distribution of risk between passengers and pilots, considering that pilots fly much more frequently than passengers.     

What is the impact of sustainable development on the re-localisation of manufacturing enterprises?

Rendering the supply chain more eco-friendly is an innovative idea progressively adopted by industry. Our research focuses on the CO₂ equivalent emissions along the supply chain due to freight energy use and storage. A supply chain model based on discrete event simulation was developed. The model uses reorder point production management policy (ROP) within a make to stock (MTS) demand response strategy. Manufacturing capability is also taken into account using an overall equipment effectiveness indicator (OEE). In addition, the location of the firms and their types of products are modelled. The purpose is to compare supply chain CO₂ equivalent emissions of different configurations. This method is applied to two industrial cases: Carrier (UTC group), a large cooler manufacturer and Zannier group, a textile industry. The principle objective of the study is to conduct pertinent experiments to give green guidelines to Carrier and Zannier group.     

Optimizing real-time vehicle sequencing of a paint shop conveyor system

A discrete event simulation model and a decision optimizer that were developed for a General Motors paint shop conveyor system are presented. The simulation model interacts with the decision optimizer at four critical points in the system, trying to regroup batches of different colored vehicles. The decision optimizer employs dynamic programming and integer programming to optimize vehicle routing policies. Simulation results of the current decision making policies are compared with those of the proposed optimized policies showing that the number of paint head changes can be significantly reduced resulting in substantial savings on paint head cleaners and paint.     

Priority Rules for Multi‐Task Due‐Date Scheduling under Varying Processing Costs

We study the scheduling of multiple tasks under varying processing costs and derive a priority rule for optimal scheduling policies. Each task has a due date, and a non‐completion penalty cost is incurred if the task is not completely processed before its due date. We assume that the task arrival process is stochastic and the processing rate is capacitated. Our work is motivated by both traditional and emerging application domains, such as construction industry and freelance consulting industry. We establish the optimality of Shorter Slack time and Longer remaining Processing time (SSLP) principle that determines the priority among active tasks. Based on the derived structural properties, we also propose an effective cost‐balancing heuristic policy and demonstrate the efficacy of the proposed policy through extensive numerical experiments. We believe our results provide operators/managers valuable insights on how to devise effective service scheduling policies under varying costs.     

Reassessing Tradeoffs Inherent to Simultaneous Maintenance and Production Planning

Previous work has considered the simultaneous (as opposed to sequential) optimization of a maintenance policy and a production policy in a multi‐product setting with random yield and product mix constraints. One of the sequential approaches to which the simultaneous approach is compared is a so‐called first‐come‐first‐served (FCFS) approach, i.e., an approach that generates randomized production policies that do not depend on the deterioration state of the machine. However, the model formulation for this approach does not generate policies consistent with this FCFS notion. Therefore, we present a revised FCFS model and analyze its performance using an existing experimental design. The results suggest that previous work overestimates the degree to which a FCFS approach is suboptimal, and underestimates the value of simultaneously optimizing the maintenance and production decisions. Lastly, we conduct additional experiments which suggest that the joint impact of using both simultaneous optimization and a deterioration dependent production policy is quite significant.