Master Scheduling in Assemble-To-Order Environments: A Capacitated Multiobjective Lot-Sizing Model

Basic characteristics of an assemble-to-order environment make effective master scheduling extremely difficult. Limited resource capacities and dynamic customer end-item demand contribute to the complexity of the master production scheduling problem. To gain flexibility and responsiveness within this system, the master production schedule (MPS) focuses at the component level. This research proposes a master scheduling technique for manufactured components which combines a multiobjective capacitated multi-item/multi-stage lot-sizing model with an interactive multiple objective optimization solution procedure. To evaluate the model's performance as a realistic and practical master scheduling tool, this study focuses on the National Cash Register (NCR) electronics manufacturing facility in Columbia, South Carolina.     

The Individually Responsible and Rational Decision Approach to Economic Lot Sizes for One Vendor and Many Purchasers: A Comment*

Joglekar and Tharthare [6] presented an alternate approach for minimizing total inventory carrying and ordering costs of a vendor and the purchaser(s). This approach permits the vendor and the purchaser(s) to rationally select their operating policies. Joglekar and Tharthare claimed that their approach is more economical than the joint lot-size approach. In this note we identify some conceptual issues in their approach and demonstrate the superiority of the joint lot-size approach with the help of an example.     

Marketing Communication Intensity Across Industries

Marketing communication intensity (i.e., the ratio of advertising and promotional expenditures to sales) has been an important topic for both business managers and academics. Here, we investigate cross-sectional and time-series variation of communication intensity due to: type of offering (product versus service) and type of market (consumer versus industrial). Overall, we find that both of these factors affect variation of communication intensity across industries and over time. However, the effect of market type is much more dramatic than the effect of offering type. Such knowledge about patterns in communication intensity levels helps managers make decisions about how much to spend on advertising and promotion.     

ANALYSIS OF ALTERNATIVE SCHEDULING POLICIES FOR HOSPITAL NURSES

The persistent shortage of nurses adversely affects the productivity, quality of care, and operating costs in most acute care hospitals. Aggravating the shortage are high nurse turnover rates, approaching 200% in some institutions. Policies to ensure adequate staffing levels and provide more attractive work schedules are alleged to improve nurse retention. However, their cost is seldom discussed. We compared expected nursing expense and workforce requirements to staff eight medical and surgical nursing units of a large hospital for 1 month, under 12 different scheduling policies alleged to improve turnover. Using simulation and an integrated staffing and scheduling methodology, we found that the expected nursing wages and workforce requirements for some policies differed by as much as 33%. In this hospital, the expected labor costs for certain policies could erode the benefits expected from improved retention. In contrast, other policies appear to allow high utilization of nursing resources, enhancing the expected benefits of reduced turnover with significant reductions in expenses for labor, recruiting, training, and fringe benefits.     

Integrative Cycle Scheduling Approach for a Capacitated Flexible Assembly System*

This study revisits the traditional single stage, multi-item, capacitated lot-sizing problem (CLSP) with a new integrative focus on problem structuring. Unlike past research, we develop integrative cycle scheduling approaches which simultaneously address lot-sizing, capacity, and sequencing issues. Our purposes are to (1) explore the effect of sequencing on inventory levels, (2) examine the problem of infeasibility in the economic lot scheduling problem (ELSP), and (3) provide a simple methodology of generating low-cost cycle schedules in an environment with discrete shipping, dynamic demands, limited capacity, zero setup cost, and sequence-independent setup times. Our procedures are compared to benchmark cycle scheduling approaches in terms of both inventory cost and computation time under different demand scenarios, using the operating data from a flexible assembly system (FAS) at the Ford Motor Company's Sandusky, Ohio plant.     

Two-Group Classification Using Neural Networks*

Artificial neural networks are new methods for classification. We investigate two important issues in building neural network models; network architecture and size of training samples. Experiments were designed and carried out on two-group classification problems to find answers to these model building questions. The first experiment deals with selection of architecture and sample size for different classification problems. Results show that choice of architecture and choice of sample size depend on the objective: to maximize the classification rate of training samples, or to maximize the generalizability of neural networks. The second experiment compares neural network models with classical models such as linear discriminant analysis and quadratic discriminant analysis, and nonparametric methods such as k-nearest-neighbor and linear programming. Results show that neural networks are comparable to, if not better than, these other methods in terms of classification rates in the training samples but not in the test samples.     

A Multivariate Indicator to Compute Middle Class Population

Social Indicators Research - Monitoring progress towards the Sustainable Development Goals by 2030 requires the global community to disaggregate targets along socio-economic lines, but little has...     

Using Multiple Methods to Provide Prediction Bands of K-12 Enrollment Projections

Population Research and Policy Review - Often, demographers charged with projecting enrollments for school districts are asked to provide a range of future enrollments, as point estimates are not...     

Evaluating social investment in disability policy

Disability policy in European countries is displaying a shift towards social investment: increasing human capital and access to the labour market. The reasoning that underlies this transition is that disabled persons would benefit from mainstream employment, but are impeded in traditional policy by deficiencies in labour supply and demand. However, the shift towards more activating policies in many countries is accompanied by a decline in social protection. It is unclear whether social investment may effectively promote the employment chances of disabled persons within this context. The present research examines this question through a quantitative, cross-sectional, multilevel analysis on microdata from 22 EU countries. Our findings suggest greater activation to predict lower employment chances, while reducing passive support shows mixed effects. Conversely, measures for facilitation in daily life predict greater employment chances, as do measures for sheltered work. These findings raise questions over the value of social investment for disabled persons—and underline the need to overcome broader barriers in the labour market and in society.