The effect of lot-sizing on workload variability

Lot-sizing models which group demand requirements for one or more consecutive time periods into a single production run have received considerable attention in recent years. Material Requirements Planning (MRP) systems must, for instance, make a lot-size decision for each planned order release. Existing decision models attempt to minimize the sum of setup plus inventory holding costs. However, lot-sizing tends to increase the work center load variability, and, consequently, the costs associated with changing production levels from period to period should be incorporated into the economic analysis. This study is concerned, first of all, with analytically describing the relationship between dynamic lot-sizing models and workload variability. Secondly, in order to account for production level change costs we propose a simple modification to existing heuristic models. Lastly, we employ a simulation model to empirically extend these results to a typical MRP multiechelon production environment. An example is included to show clearly that with cost premiums for overtime and severance or guaranteed minimum costs for undertime the traditional lot-sizing techniques significantly underestimate actual costs and can lead to very costly policies.Mean, variance and coefficient of variation of period work time requirements are derived as a function of several algorithm characteristics. Average cycle time (number of periods covered by a single batch) is found to be the most influential factor in determining workload variability. Variance grows approximately in proportion to this cycle time with the proportionality constant being the square of average period workload. Cycle time and demand variability also contribute to workload variability. Results indicate that for a given average cycle time, the EOQ method will minimize workload variability. When N products utilize the same work center, the coefficient of load variation will be reduced by a factor of N^{?$\text{1}\text{2}$} unless requirements are positively correlated. Positive correlation would result when products have similar seasons or parent items. In this case grouping such products cannot help reduce variability.In order to incorporate production level change costs into existing heuristics we may simply introduce a term consisting of a penalty factor times average cycle time. The penalty factor represents the costs of period by period production level changes. Several popular heuristics are extended in this fashion, and it is found that solutions are still readily obtainable, requiring only modifications to setup or holding cost parameters.The effects of level change costs are examined via simulation for a specific yet typical environment. It is found that when setup costs are significant, traditional lot-sizing heuristics can provide cost savings and service level improvements as compared to lot-for-lot production. However, whereas for our model the obtainable profit improvement from lot-sizing was 25% in the case of freely variable capacity, actual improvements were only one half as large when reasonable hiring and firing practices and overtime and undertime costs were considered. Consequently, management needs to consider carefully labor costs and work center product relationships when determining a production scheduling method.     

The use of workload information to control job lateness in controlled and uncontrolled release production systems

The performance of a workload dependent scheduling and due date assignment rule is investigated. The rule uses time-phased workload information and time-phased capacity information. Performance comparisons are made with a rule that uses only time-aggregated workload information. The performance for two methods of releasing jobs to the shop is investigated: an uncontrolled method where the jobs are released at random, and a controlled method where jobs are released to maintain a specific workload norm. Computer simulation is used as the research tool. The mean and standard deviation of lateness are used as performance measures.The results indicate that the use of time-phased workload information may decrease the variance of the lateness, as compared with the use of time-aggregated workload information only. However, the magnitude of the effect depends on the type of sequencing rule used. Furthermore, if time-phased information is used, control of the mean lateness requires that the amount of capacity available for loading used in the loading procedure differs from the amount of capacity actually available for production. It is shown that by selecting adequate parameter values, both a constant mean lateness and a small variance of lateness can be obtained with this type of assignment rule.These results are valid for both types of release situations. So even in the case where the workload of the shop is under strict control, and the mean operation flow time does not, therefore, vary, the use of time-phased workload information can decrease the variance of the lateness.     

Currently practiced formulations for the assembly line balance problem

New formulations for the assembly line balance problem are proposed based on interviews and surveys of practicing engineers. These formulations are the basis for a model in goal programming form. A branch-and-bound algorithm is developed which can solve the model for an optimum solution. Computational studies show that computer run time is very modest for moderate size problems.Interviews and a survey of practicing engineers were used to develop a list of goals or constraints germane to the assembly line balance problem. These included minimizing working areas or employees, making sure tasks assigned to a station do not exceed the cycle time, and adhering to sequence constraints. These constraints are included in most traditional models. However, additional goals were mentioned. These included avoiding changes in workload assigned to a work area, adhering to layout requirements of the plant, making combinations of tasks interesting, avoiding the combination of physiologically demanding tasks, etc.The additional goals above are incorporated in a new formulation for the assembly line balance problem. This formulation is in goal programming form. The goal programming model attempts to minimize deviations from goals. If deviations are necessary, lowest ranked goals are violated first. The objective function of the model is based on an ordinal ranking of goals only. The survey mentioned above showed that engineers did not find it difficult to rank the importance of goals.The proposed goal programming model is a mixed integer linear program. Previous studies have shown that cutting plane and implicit enumeration techniques are inferior to branch-and-bound algorithms. A branch-and-bound method, called GoalOriented Algorithm for Line Balance (GOAL), is developed to solve the formulations proposed in the paper.GOAL was computationally tested with 50 problems. These problems varied in size from 4 to 35 tasks. One of the problems was an engine cradle assembly problem encountered by an automobile manufacturer. Computer run times appeared reasonable. For example, the engine cradle problem 35 tasks) required only 16.3 seconds CPU on the DEC PDF at California State University, Northridge. GOAL's execution time appeared linearly proportional to the number of tasks required for most problems.     

An analysis of university year-round operation

The implementation of year-round operation has often been suggested as a means for accommodating additional demand for student admissions at a university campus of fixed capacity. However, because the student flow process at a university has not been well understood, many institutions have been disappointed to find the actual benefits resulting from the addition of a regular summer program of instruction to be far less than they had expected. This paper demonstrates that, due to established patterns of student attendance, a reasonable expectation of a change to year-round operation is that the undergraduate admission rate will increase by 5 per cent when enrollment is held fixed. Moreover, the summer term will attract only one-third as many undergraduate students as are enrolled during the regular academic year. These computations assume that no attempt is made to exert control over student attendance patterns.A queueing model is developed that relates the admission rate to the proportion of students who belong to various cohorts with common workload requirements and attendance patterns. Data gathered at the University of California, Berkeley campus is used to estimate these proportions for a campus which offers a year-round program. From these estimates are derived values for the overall admission rate and the ratio of summer enrollment to average nonsummer enrollment. These values are then compared with those obtained for a campus of like size which does not offer a year-round program of instruction. The paper concludes that, unless an institution is willing to exert control over student attendance patterns, university year-round operation is probably not economical in a society which places heavy emphasis on the summer as a time when students should vacation or take temporary jobs.     

单调作业中人因失误模式分析

文章结合脑力负荷理论和人因工程理论,设计模拟单调作业的人机交互实验,采用统计控制图分析持续单调作业过程中被试的脑力负荷变化,研究人因失误过程中被试的操作状态和失误模式。结果显示：（1）单调作业过程中不同作业时间段对被试的任务反应速率和正确率有显著影响。（2）当被试出现脑力超负荷时,通常采用延长反应时间的策略,来改善脑力负荷;（3）通过延长反应时间的策略,对于改善脑力负荷状态和避免人因失误有明显作用;（4）惯性操作是单调作业的人机系统出现人因失误的主要原因。     

Changes in urban land values: 1836–1970

A model is developed for measuring the return to holding land and those returns are examined using a random coefficient estimation procedure for specific periods from 1836 to 1970. This statistical model provides a mean rate of return for land and a predictor for each time period. The results suggest that the long-term return to holding land is no higher than the rate of return to holding high-grade bonds. For shorter holding periods, the returns vary significantly.     

基于时间约束的单产品共同配送研究

随着物流业的调整发展．提高物流效率、降低物流成本逐渐成为关注的焦点。有着发达物流业的国家,如德国、美国等的实践已经证实,采用共同配送这一先进的配送模式,将能够改善在物流效率、物流成本方面所凸现的问题。在我国,共同配送体系还不完善,加之客户对于配送时间的要求也越来越高．满足客户时间要求的集约化、协同化配送就成为亟待解决的问题。文章针对这一问题,将“软时间窗”和“硬时间窗”同时引入到共同配送中,建立模型并通过算例分析对理论研究进行了实证。     

Optimizing the spatial assignment of schools to reduce both inequality of educational opportunity and potential opposition rate through introducing random mechanism into proximity-based system

A serious spatial inequality of educational opportunity was revealed worldwide, for wealthy families can access good schools by buying real estate with good school' enrollment quota. Although the existing studies had revealed that random-based school assignment can significantly improve equality of opportunity allocation, random mechanism was adopted only in few places. Two major resistances of introducing random mechanism exist: the possibility of increased commuting distance to schools and the effected relative beneficiaries. In order to make the random-based allocation more feasible, this study proposes a spatial optimization model to take these two factors into account into proximity-based school assignment system. The proposed multi-objective allocation model, with the constraint conditions of assigning students to 3 closest schools and school capacities, was developed in this study to minimize the spatial disparity of educational opportunity and the potential opposition rate of introducing random mechanism into proximity-based assignment system. The model will be solved by a heuristic algorithm and applied to a case study area of Shijingshan District, Beijing. The results showed that the proposed model could improve spatial equality of educational opportunity significantly, but along with a minor increase on commuting distance to schools. In addition, potential opponents of introducing random mechanism decrease as the weight of parameters related to opposition rate increases in the model, reducing nearly 10% in the best case. Therefore, the solutions provided by proposed model may encounter less resistance in a democratic voting system. However, the results also indicated that there would be some relative beneficiaries who may oppose introducing random mechanism into proximity-based school system even in the best case. This implies that, to achieve equal educational opportunity in the context of proximity-based school system, optimized allocation is needed along with a more even distribution of educational resources.     

Forecasting inflation using time‐varying Bayesian model averaging

This paper presents a Bayesian model averaging regression framework for forecasting US inflation, in which the set of predictors included in the model is automatically selected from a large pool of potential predictors and the set of regressors is allowed to change over time. Using real‐time data on the 1960–2011 period, this model is applied to forecast personal consumption expenditures and gross domestic product deflator inflation. The results of this forecasting exercise show that, although it is not able to beat a simple random‐walk model in terms of point forecasts, it does produce superior density forecasts compared with a range of alternative forecasting models. Moreover, a sensitivity analysis shows that the forecasting results are relatively insensitive to prior choices and the forecasting performance is not affected by the inclusion of a very large set of potential predictors.     

Impact study on the interest rate futures market

Any announcement from the Federal Reserve has a huge impact on the interest rate markets. The press releases from the Federal Open Market Committee (FOMC) are major inputs to the market and the random intervention model is applied to interest rate futures transaction data to measure FOMC announcement impact. Missing prices during non-trading time periods are imputed iteratively during the estimation of model parameters. The study shows that the market trading on the announcement day is different from the market trading on a non-announcement for both the Eurodollar and T-Note futures market.     

Modelling security market events in continuous time: Intensity based,multivariate point process models

A continuous time econometric modelling framework for multivariate financial market event (or ‘transactions’) data is developed in which the model is specified via the vector conditional intensity. Generalised Hawkes models are introduced that incorporate inhibitory events and dependence between trading days. Novel omnibus specification tests based on a multivariate random time change theorem are proposed. A bivariate point process model of the timing of trades and mid-quote changes is then presented for a New York Stock Exchange stock and related to the market microstructure literature. The two-way interaction of trades and quote changes in continuous time is found to be important empirically.     

A Bayesian approach to imposing curvature on distance functions

The estimated parameters of output distance functions frequently violate the monotonicity, quasi-convexity and convexity constraints implied by economic theory, leading to estimated elasticities and shadow prices that are incorrectly signed, and ultimately to perverse conclusions concerning the effects of input and output changes on productivity growth and relative efficiency levels. We show how a Bayesian approach can be used to impose these constraints on the parameters of a translog output distance function. Implementing the approach involves the use of a Gibbs sampler with data augmentation. A Metropolis–Hastings algorithm is also used within the Gibbs to simulate observations from truncated pdfs. Our methods are developed for the case where panel data is available and technical inefficiency effects are assumed to be time-invariant. Two models—a fixed effects model and a random effects model—are developed and applied to panel data on 17 European railways. We observe significant changes in estimated elasticities and shadow price ratios when regularity restrictions are imposed.     

基于重心法的应急物流中心选址初探

文章针对应急物流系统对时间的特殊要求,利用重心法建立了应急物流中心的选址模型。结果表明:重心法是一种简便、工作量较小的方法,能较好地简化应急物流中心的选址问题,具有较强的实用性。     

Environmental Change, Leadership Succession and Incrementalism in Local Government

A theoretical model of strategic budgetary choices in local government is developed and tested. The model assumes that expenditure decisions are a function of changes in environmental circumstances and the characteristics of local leaders. Environmental change is operationalized through measures of workload, munificence and regulatory controls. Leadership succession is defined as the turnover in managerial and political élites. These environmental and leadership variables are included in a multivariate statistical model of budgetary incrementalism. The model is tested on the spending decisions of 402 English local authorities from 1981 to 1996. The empirical results suggest that the extent of budgetary change is influenced strongly by environmental change but weakly by leadership succession. Furthermore, environmental constraints became tighter during the study period. The characteristics of public sector organizations that impose limits on the strategic choices of new leaders are identified.     

Specification diagnostics based on Laguerre alternatives for econometric models of duration

Score tests of the null hypothesis of exponentially distributed durations (conditional on regressors) against alternatives in a family of approximations to arbitrary distributions for non-negative random variables are developed. The test statistics take a simple, easily calculated and interpreted form. The alternatives considered are expansions of various orders in Laguerre polynomials. An economic model generating exponential unemployment duration is presented. The statistics are applied in a look at unemployment durations in the Denver Income Maintenance Experiment data.     

Monotone missing data and pattern-mixture models

It is shown that the classical taxonomy of missing data models, namely missing completely at random, missing at random and informative missingness, which has been developed almost exclusively within a selection modelling framework, can also be applied to pattern-mixture models. In particular, intuitively appealing identifying restrictions are proposed for a pattern-mixture MAR mechanism.     

Project appraisal for developing countries: a systematic approach

A cost/benefit model has been developed for financial and economic appraisal of projects in developing countries. The approach proposed is a technique for analysis that forces the analyst to consider all the relevant factors systematically, thus enhancing the identification of problem areas and supporting rational disciplined decision-making processes. The model includes all the assumptions relevant to the project analysis, detailed financing, financial analysis, the impact of the project on public finance, the impact on foreign exchange, and the economic appraisal from the nation's point of view.

The model is developed at a sufficiently detailed level and proves to be very useful for short-term/long-term planning and evaluation of the project. Consistency of making assumptions is ensured by having all the assumptions clearly defined and shown in the model. Moreover, the structure of the model is flexible and can easily be upgraded over time to meet the requirements and refinements with availability of more information and changing conditions. It is felt that with the existence of an easy to use computer model reluctance or indifference to test alternatives and carry out sensitivity analysis, which continues to the detriment of the nation's interest, will be eliminated.     

A lot sizing and sequencing algorithm for dynamic demands upon a single facility

A heuristic algorithm is developed and applied to determine lot sizes and production sequence on a single facility. The various product demands are treated as deterministic and time varying (dynamic) over a finite planning horizon, such as that generated from a material requirements planning (MRP) system.In contrast to other approaches available, the algorithm considers the sequencing decision in each period by realistically assuming inventory holding cost occurrence in the period of production, and in addition, it is capable of considering set-up times where such set-up times consume available productive capacity. The ability to handle numerous products, and the capability of being able to specify maintenance time and holidays is an integral aspect of the algorithm.The results of an application of the algorithm in a medium size bearing company have shown very significant reduction in the controllable inventory holding cost while eliminating late deliveries. In an effort to cope with potential realistic schedule alterations, different solutions were developed for managerial evaluation providing greater flexibility but at a higher cost.     

A Note on Estimated Coefficients in Random Effects Probit Models

This note points out to applied researchers what adjustments are needed tothe coefficient estimates in a random effects probit model in order to make valid comparisons in terms of coefficient estimates and marginal effects across different specifications. These adjustments are necessary because of the normalization that is used by standard software in order to facilitate easyestimation of the random effects probit model.     

The random coefficients logit model is identified

The random coefficients multinomial choice logit model, also known as the mixed logit, has been widely used in empirical choice analysis for the last thirty years. We prove that the distribution of random coefficients in the multinomial logit model is nonparametrically identified. Our approach requires variation in product characteristics only locally and does not rely on the special regressors with large supports used in related papers. One of our two identification arguments is constructive. Both approaches may be applied to other choice models with random coefficients.