汇率的就业传导渠道及其效应测算——基于中国制造业面板数据的实证研究

文章研究了汇率的就业传导渠道,及其行业异质性。本文基于传统的生产函数理论,通过建模和理论分析得出:汇率影响就业的传导渠道主要有出口需求、资源配置和效率的三渠道。并基于中国制造业30个行业的2003年至2009年的面板数据,运用残差替代法和面板平滑机制转换回归,测算出各传导渠道在汇率影响就业过程中所起到的作用,结果表明:在整个传导机制中,出口需求对就业的作用较强,效率渠道和资源配置作用相对较弱;人民币升值对就业的总体效应为负效应,且传导机制中各渠道均具不同程度不同特征的行业异质性。     

Multi-Item, Multi-Facility Supply Chain Planning: Models, Complexities, and Algorithms

We propose a planning model for products manufactured across multiple manufacturing facilities sharing similar production capabilities. The need for cross-facility capacity management is most evident in high-tech industries that have capital-intensive equipment and a short technology life cycle. We propose a multicommodity flow network model where each commodity represents a product and the network structure represents manufacturing facilities in the supply chain capable of producing the products. We analyze in depth the product-level (single-commodity, multi-facility) subproblem when the capacity constraints are relaxed. We prove that even the general-cost version of this uncapacitated subproblem is NP-complete. We show that there exists an optimization algorithm that is polynomial in the number of facilities, but exponential in the number of periods. We further show that under special cost structures the shortest-path algorithm could achieve optimality. We analyze cases when the optimal solution does not correspond to a source-to-sink path, thus the shortest path algorithm would fail. To solve the overall (multicommodity) planning problem we develop a Lagrangean decomposition scheme, which separates the planning decisions into a resource subproblem, and a number of product-level subproblems. The Lagrangean multipliers are updated iteratively using a subgradient search algorithm. Through extensive computational testing, we show that the shortest path algorithm serves as an effective heuristic for the product-level subproblem (a mixed integer program), yielding high quality solutions with only a fraction (roughly 2%) of the computer time.     

Sequencing and scheduling in flowshops with task redistribution

In some manufacturing situations, station tasks or operations can be shifted or redistributed to adjacent stations. This can be done when these stations have the appropriate equipment, and the workers on that station can perform the shifted work to a reasonable level of competency. This paper addresses such an environment and provides a general framework for applying the shifting or redistribution of tasks methodology to the intermediate storage, no-intermediate storage and no-wait flowshop problems. The outcome of this research is a way in which to utilise more efficiently the general-purpose facilities of this type of production environment. It includes mathematical models, recurrence equations and solution techniques for sequencing and scheduling. From an extensive numerical investigation, the benefits achieved by the application of this methodology are detailed.     

The relationships among virtual enterprise,information technology,and business performance in agile manufacturing: An industry perspective

Agile Manufacturing (AM) is a manufacturing paradigm that focuses on smaller scale, modular production facilities, and agile operations capable of dealing with turbulent and changing environments. From several enablers of AM, Virtual Enterprise (VE) and Information Technology (IT) were chosen. This empirical study explored the impact of the alignment between VE and IT on business performance in an AM setting for five different industries. Extensive data collection strategy and several tests were used to establish the reliability and validity of the data collected. Extensive analyses of the data using Structural Equation Modeling were performed for five hypotheses across five different industries. The results indicate that both VE and IT had positive influences on business performance for all industries. It was also established that the alignment between VE and IT had a positive impact on business performance for all industries. Further, it was shown that the impact of the alignment between VE and IT on business performance was more significant than the impact of VE and IT on business performance individually for all industries. The statistical analyses and results showed that there were no significant differences among the industries surveyed. At the bivariate level of analysis, some minor differences for one industry were highlighted. In conclusion, the assessment of the results along with future research directions is provided.     

河北省装备制造产业发展的灰色关联分析

基于灰色系统中的关联分析方法,从动态的视角出发,对河北省装备制造产业生产总值与装备制造产业系统内部结构关系进行研究分析,得出河北省装备制造产业的发展具有以下特点:金属制品业等资源加工型产业依旧在装备制造产业中占据主导地位,通用装备业和仪器仪表业等技术密集型产业的贡献率相对不足.因此,应从河北省的实际情况出发,不断优化装备制造的内部产业结构。     

Order selection optimization in hybrid make-to-order and make-to-stock markets

The order selection process for firms operating in markets characterized by standard products as well as strong product customization, is directly tied to the customer and to the associated production costs. This order selection process must be inter-functional with marketing and manufacturing in deciding which orders to accept, specially since the selection criteria used by marketing and manufacturing tend to differ. This paper develops a methodology/mathematical programming model for improving this coordination through an optimal selection of sales orders, such that the total financial contribution of selected orders is maximized. Based on an actual case study in the pigment manufacturing industry, the methodology provides for a user interface that addresses both the manufacturing and marketing department. More importantly, such a marketing/production coordination allows for improved performance in increasingly segmented (customized) markets, while continuing standard product lines as well.     

A new lot sizing and scheduling heuristic for multi-site biopharmaceutical production

Biopharmaceutical manufacturing requires high investments and long-term production planning. For large biopharmaceutical companies, planning typically involves multiple products and several production facilities. Production is usually done in batches with a substantial set-up cost and time for switching between products. The goal is to satisfy demand while minimising manufacturing, set-up and inventory costs. The resulting production planning problem is thus a variant of the capacitated lot-sizing and scheduling problem, and a complex combinatorial optimisation problem. Inspired by genetic algorithm approaches to job shop scheduling, this paper proposes a tailored construction heuristic that schedules demands of multiple products sequentially across several facilities to build a multi-year production plan (solution). The sequence in which the construction heuristic schedules the different demands is optimised by a genetic algorithm. We demonstrate the effectiveness of the approach on a biopharmaceutical lot sizing problem and compare it with a mathematical programming model from the literature. We show that the genetic algorithm can outperform the mathematical programming model for certain scenarios because the discretisation of time in mathematical programming artificially restricts the solution space.     

Regional concentration and efficiency in Mexican manufacturing

This paper explores the link between industrial location, concentration, and economic efficiency in Mexican manufacturing. Using a linear programming approach, the authors calculate indices of overall, technical, allocative, and scale efficiency for Mexican manufacturing industries by state to test whether, in 1985, those regions with high levels of industrial concentration were suffering from the costs of congestion. The evidence suggests that, at least at the aggregate level, there continued to be a positive relationship between industry concentration and efficiency in production. There is also evidence that overall efficiency was related to scale efficiency, although highly industrialized regions on the production frontier often operated at inefficient scales. In particular, the most concentrated regions (the Federal District, the state of Mexico, Jalisco, and Nuevo León) consistently display decreasing returns to scale, indicating that the process of industrial concentration may be leading to diseconomies of scale. Finally, an econometric analysis suggests that scale, urbanization, and agglomeration economies are positively related to overall and technical efficiency at the regional level, while foreign ownership is negatively related. Agglomeration economies at the industry level were not significant. The paper also makes a methodological contribution. It is the first application of a distance-function production methodology to measuring regional efficiency in a developing country. It demonstrates how to conduct distance-function efficiency analysis using the newly developed GAMS mathematical programming environment. These tools should be of considerable interest to applied microeconomists.     

An Empirical Study on Measuring Industrial Competitiveness

This paper discusses the methodology developed for the Industrial Development Bank of Turkey for the purpose of measuring the competitiveness of local manufacturing firms in foreign markets. First, an industrial competitiveness model which incorporates both the firm's and foreign competititors' input costs, technological characteristics and political-economic environments is summarized. Then an application of this model to 30 selected local firms in textiles, stone and soil, and food industries is described. The results indicate that some of the selected firms are quite competitive in European, North African and Middle Eastern countries, and can export to these markets without much difficulty. Moreover, the methodology employed in this study promises to be useful in identifying the weaknesses and strengths of industries, albeit in general terms, to formulate government policies.     

Solving a concrete sleepers production scheduling by genetic algorithms

PRECON S.A. is a manufacturing company devoted to produce prefabricated concrete parts for several industries as railway transportation and agricultural industries. Recently, PRECON S.A. signed a contract with RENFE, the Spanish National Railway Company, to manufacture pre-stressed concrete sleepers for the sidings of the new railways of the high speed train (AVE). The scheduling problem associated with the manufacturing process of the sleepers is very complex, since this involves several constraints and objectives. These constraints are related to production capacity, the quantity of available moulds, demand satisfaction and other operational constraints. The two main objectives are related to the way to maximize the utilization of manufacturing resources and minimize mould movements. We developed a deterministic crowding genetic algorithm for this multiobjective problem. The algorithm has proved to be a powerful and flexible tool to solve large-scale instances of this real and complex scheduling problem.     

Controlling Rota Scheduled Production by Adjusting Stock Requirements

The paper considers a firm manufacturing several thousand different products, each requiring manufacturing time on several of its available production facilities. Production is scheduled according to a week-by-week rota, arranged so as to generate even average work loads on each production facility. Fluctuations in sales demands, however, lead to a discrepancy between the stock requirements in any section of the rota and the production capacities available. Consequently, to avoid the rota becoming disorganized, some form of production control must be applied. Since the production capacities are largely fixed, this must consist of adjusting the stock requirements. A method of computing adjusted requirements which minimizes a weighted sum of squares of the adjustments made is described. The method is based on Wolfe's technique for quadratic programming, modified to make it computationally feasible in the situation considered which involves several thousand non-negative and usually non-zero variables.     

Towards the development of human work-performance standards in futuristic man-machine systems: A fuzzy modeling approach

Drastic changes in the nature of industrial work force, from manufacturing related industries to service and information industries, and increased automation have led to abundance of jobs for which there are no established performance standards. While work performance standards exist for physical tasks that are routinely performed in manufacturing industries, limits on acceptable levels of work are yet to be developed for mental tasks which are fast becoming common. This paper describes an approach to quantify qualitative human responses and describes a procedure to integrate them with other quantitative responses resulting from physical, mental, behavioral, or physcho-social factors. The theory of fuzzy sets and systems is utilized in developing the modeling concept which can be used in developing work-performance standards or optimizing overall man—machine systems effectiveness.     

Scheduling and control,performance measures and discrete event simulation

There are a growing number of finite capacity scheduling tools which are in use and available to industry. To be fully effective, a scheduling system needs to be incorporated within a control methodology which enables shop-floor performance to be analysed and, when necessary, corrective actions to be formulated. Manufacturing system performance, however, is not only dependent upon short-term planning decisions, but is also constrained by the capability for which it is designed. Hence, any control methodology should be based on a consistent set of performance measures and well defined procedures which help to integrate decision making at all levels in the order fulfilment process. The paper examines the distinctive roles of process optimisation and process control in the decision hierarchy; it classifies a set of measures of performance and other system variables according to the functions they serve in manufacturing control, and suggests a hierarchical process control methodology. The role of discrete event simulation techniques in linking decisions on manufacturing system design and production planning/control is also discussed.     

Scheduling of continuous and discontinuous material flows with intermediate storage restrictions

This paper deals with scheduling batch (i.e., discontinuous), continuous, and semicontinuous production in process industries (e.g., chemical, pharmaceutical, or metal casting industries) where intermediate storage facilities and renewable resources (processing units and manpower) of limited capacity have to be observed. First, different storage configurations typical of process industries are discussed. Second, a basic scheduling problem covering the three above production modes is presented. Third, (exact and truncated) branch-and-bound methods for the basic scheduling problem and the special case of batch scheduling are proposed and subjected to an experimental performance analysis. The solution approach presented is flexible and in principle simple, and it can (approximately) solve relatively large problem instances with sufficient accuracy.     

Locating and capacity planning for retailers of a new supply chain to compete on the plane

This paper investigates the network design problem of a two-level supply chain (SC), which is applicable for industries such as automotive, fuel and tyre manufacturing. Models presented in this paper aim at locating retail facilities of an SC and identifying their required capacities in the presence of existing competing retailers of a rival SC. We consider feasible locating space of the retail facilities on the continuous plane with bounded constraints and static competition among the rivals of the markets with deterministic demands. The problem is used for both essential and luxury product cases; hence, we consider elastic and inelastic demands, both. The models discussed in this paper are non-linear and non-convex which are difficult to solve. We use interval branch-and-bound as optimization algorithm for small size single-retailer problems, but for large-scale, multi-retailer problems we need to have more efficient methods. Therefore, we apply a heuristic algorithm (H1), a simulated annealing (SA) algorithm, an interior point (IP) algorithm, a genetic algorithm (GA) and a pattern search algorithm for solving multi-retailer problem with elastic and inelastic demands. Computational results obtained from performing different solution approaches for both elastic and inelastic show that mostly IP, PS, and H1 methods outperform the other approaches. The computational results on a real-life case are also promising. Several extended mathematical models and an example of a typical case with details are presented in the appendices of the paper.     

Measuring the performance of operations of Hong Kong's manufacturing industries

The relative operational performance of Hong Kong's manufacturing industries is measured and analyzed for the period from 1987 to 1993. The measurement technique used is the recently developed operational competitiveness rating (OCRA) procedure. The comparison of the overall operational performance of Hong Kong's nine manufacturing industry groups is based on the OCRA computations of relative resource consumption and revenue generation performance. The implications of OCRA results in terms of industry performance trends are discussed and strategic issues are reviewed.     

Location of slaughterhouses under economies of scale

The facility location problem described in this paper comes from an industrial application in the slaughterhouse industry of Norway. Investigations show that the slaughterhouse industry experiences economies of scale in the production facilities. We examine a location-allocation problem focusing on the location of slaughterhouses, their size and the allocation of animals in the different farming districts to these slaughterhouses. The model is general and has applications within other industries that experience economies of scale.We present an approach based on linearization of the facility costs and Lagrangean relaxation. We also develop a greedy heuristic to find upper bounds. We use the method to solve a problem instance for the Norwegian Meat Co-operative and compare our results to previous results achieved using standard branch-and-bound in commercial software.     

Quality Assurance of a Maker-Packer Model

We study a maker-packer production system in cigarette manufacturing where two different types of detectors are installed on the making and packing machines to maintain the product quality. The making machine detector has a continuously adjustable setting which determines the proportion of defective cigarettes removed. The packing machine detector has only discrete settings. We develop an economic model to derive the optimal settings for these detectors to achieve a specified average outgoing quality. The proposed maker-packer model is useful in other industries.     

制造单元布局问题的双目标模型与算法研究

单元制造系统的布局对于提高系统的效率起着十分重要的作用。以最小化物料周转量和设施面积为目标,建立了一个单元制造系统布局的双目标优化模型,在该模型中不同制造单元的布局、单元内部不同设施的位置与方向这几个问题可以同时进行优化。基于模拟退火邻域解的变尺度生成机制和双目标抽样准则设计了模型的求解算法。算例表明本文算法所得Pareto解集优于经典的NSGA-Ⅱ算法。