Standard Container Size Discounts and the Single-Period Inventory Problem*

This paper analyzes the problem of choosing the optimal order quantity and its associated number of standard containers making up the order for single-period inventory models under standard container size discounts. A range is determined that contains the optimal order quantity. Two algorithms are presented. The first algorithm solves the general case in which there is no restriction on the types of containers included in an order. The second algorithm solves a more restricted policy that requires the buyer to accept the order with successively smaller container sizes.     

SOME COMMENTS ON “A SYSTEMS PERSPECTIVE ON MATERIALS REQUIREMENTS PLANNING”*

We believe there are some serious deficiencies in the Morecroft article on MRP problems which appeared in a recent issue of this journal. The article, at the most, shows that MRP, inappropriately imposed on an existing production system, can result in undesirable system performance. This does not represent a new or startling conclusion. Four problem areas in the article are discussed, and suggested alternative approaches are offered.     

AN ANALYSIS OF CAPACITY PLANNING PROCEDURES FOR A MATERIAL REQUIREMENTS PLANNING SYSTEM*

This paper is concerned with planning work-center capacity levels in manufacturing firms that employ a material requirements planning (MRP) system. It presents four procedures for developing work-center capacity plans designed to insure the production of components and assemblies as specified by the MRP plan and the master production schedule (MPS). These procedures (capacity planning using overall factors, capacity bills, resource profiles, and capacity requirements planning) are compared using simulation analysis. The results indicate that the performance of a procedure when measured against the MPS depends on the operating conditions of the manufacturing system. The results also indicate that the choice of a particular procedure often represents a compromise among the benefits of improved MPS performance, the costs of preparing and processing data, and the premium expenses required for more frequent adjustments in work-center capacity levels.     

The additive hazards model with high-dimensional regressors

This paper considers estimation and prediction in the Aalen additive hazards model in the case where the covariate vector is high-dimensional such as gene expression measurements. Some form of dimension reduction of the covariate space is needed to obtain useful statistical analyses. We study the partial least squares regression method. It turns out that it is naturally adapted to this setting via the so-called Krylov sequence. The resulting PLS estimator is shown to be consistent provided that the number of terms included is taken to be equal to the number of relevant components in the regression model. A standard PLS algorithm can also be constructed, but it turns out that the resulting predictor can only be related to the original covariates via time-dependent coefficients. The methods are applied to a breast cancer data set with gene expression recordings and to the well known primary biliary cirrhosis clinical data.     

Are Psychology University Student Gamblers Representative of Non-university Students and General Gamblers? A Comparative Analysis

Students recruited from psychology undergraduate university populations are commonly used in psychology research, including gambling studies. However, the extent to which the use of this subpopulation produces findings that can be extrapolated to other groups is questionable. The present study was designed to compare results from university-recruited psychology student gamblers to those obtained from a sample of gamblers recruited from the general population that also included students. An online survey measuring gambling behavior and Internet gambling, attitudes and knowledge about gambling and problem gambling severity was posted on websites accessed by gamblers. Participants were recruited from two sources, a psychology undergraduate university population (n = 461) and online websites (n = 4,801). Results showed university-recruited students differed significantly from both adults and students recruited from the general population in respect to demographic variables and gambling behavior. Psychology undergraduate students were younger, more likely to be female, and had lower incomes. When relevant demographic variables were controlled, psychology undergraduate students were found to gamble less frequently, at different times, and to be at lower-risk for gambling-related problems, but had more irrational beliefs and more negative attitudes towards gambling than gamblers recruited from the general population. Results suggest that caution should be used in extrapolating findings from research using university-recruited psychology student gamblers to wide community populations due to differences related to gambling thoughts, attitudes and behaviors.