A multistage approach for production and workforce planning in long-cycle product environments

Aggregate production planning (APP) has been studied extensively for the past two decades. The APP problem, also called production and workforce scheduling, is to determine the optimal workforce and production level in each period of the planning horizon in order to satisfy demand forecasts for these periods. The advantages of the APP are low cost of data collection and computational cost of the running model; the accuracy of data; and, effective managerial understanding of the results. If the product of concern takes longer than one period, it is called a long-cycle product. Examples of long-cycle products are aircraft, ships, buildings and special machines. A detailed model incorporating dynamic productivity and long-cycle products considerations is presented to solve the problem of production and workforce planning. Using a multistage production system approach, a search technique is developed to solve this class of problems where the objective function is linear and some of the constraint coefficients are dynamically nonlinear. The model provides a better solution than an aggregate production planning model, often used to solve these problems.     

SOCIAL PREFERENCES AND TAX POLICY DESIGN: SOME EXPERIMENTAL EVIDENCE

This article reports the results of a set of experiments designed to examine whether a taste for fairness affects people's preferred tax structure. Using the Fehr and Schmidt model, we devise a simple test for the presence of social preferences in voting for alternative tax structures. The experimental results show that individuals demonstrate concern for their own payoff and inequality aversion in choosing between alternative tax structures. However, concern for redistribution decreases as the deadweight loss from progressive taxation increases. Our findings have important implications for tax policy design. ( JEL C92, D63, H21, H23)     

AN IMPROVED HEURISTIC FOR STAFFING TELEPHONE CALL CENTERS WITH LIMITED OPERATING HOURS

Many telephone call centers that experience cyclic and random customer demand adjust their staffing over the day in an attempt to provide a consistent target level of customer service. The standard and widely used staffing method, which we call the stationary independent period by period (SIPP) approach, divides the workday into planning periods and uses a series of stationary independent Erlang‐c queuing models—one for each planning period—to estimate minimum staffing needs. Our research evaluates and improves upon this commonly used heuristic for those telephone call centers with limited hours of operation during the workday. We show that the SIPP approach often suggests staffing that is substantially too low to achieve the targeted customer service levels (probability of customer delay) during critical periods. The major reasons for SIPP‘ s shortfall are as follows: (1) SIPP's failure to account for the time lag between the peak in customer demand and when system congestion actually peaks; and (2) SIPP’ s use of the planning period average arrival rate, thereby assuming that the arrival rate is constant during the period. We identify specific domains for which SIPP tends to suggest inadequate staffing. Based on an analysis of the factors that influence the magnitude of the lag in infinite server systems that start empty and idle, we propose and test two simple “lagged” SIPP modifications that, in most situations, consistently achieve the service target with only modest increases in staffing.     

Automated simulation modelling and analysis for manufacturing systems

Simulation is extensively used as a basis for the analysis and design of manufacturing systems. It has been steadily increasing in popularity due to the simplicity and ease of model understanding even by the non-simulationist. The popularity of simulation is also due to recent developments of easy-to-use simulation software. Simulation generators represent a significant trend in this direction. More recent developments include simulation expert systems both from the viewpoint of modelling and also statistical output analysis. The work that has been explained herewith is based on one such simulation generator that has been developed at the Center for Manufacturing Productivity and Technology Transfer at Rensselaer Polytechnic Institute. This system, RENSAM (RENssclaer Simulator for Automated Manufacturing) is an adaptive simulation generator and has an underlying structure that represents a FMS. The research that has been accomplished is the result of the constant efforts that are being undertaken to make RENSAM a complete decision making tool. In order to achieve what is envisioned, output analysis, optimization and sensitivity analysis routines have been added to the generic simulation and intelligent front end (IFE), The output analysis routine determines the experimental conditions under which the simulation is executed. The optimization routine searches for the optimal values for the parameters of interest and then sensitivity analysis is used to examine the relationship among various parameters. The sensitivity analysis that is presented has been developed taking into account various methodologies in this field.     

Linking Science to Common Sense

The distinction between the reified universe of science and the consensual universe of common sense introduced by Serge Moscovici in the Psychoanalysis and reiterated in further texts always gave rise to debate and puzzled interrogations. In the present text it is argued that for Serge Moscovici there is both a discontinuity and continuity between the two fields of science and common sense although at different levels of analysis. They would be discontinuous at the operative theoretical level corresponding to the logic of verification in the sense of Popper. Truth and truthfulness are not the same. But there would be continuity at the metatheoretical thematic level, where either scientists or lay people seem to follow the same non conscious insightful processes enabling them to look beyond the empirical observables as well as beyond the traditional beliefs and common places.     

WELFARE IMPACT OF A BAN ON CHILD LABOR

This article presents a new rationale for imposing restrictions on child labor. In a standard overlapping generation model where parental altruism results in transfers that children allocate to consumption and education, the Nash‐Cournot equilibrium results in suboptimal levels of parental transfers and does not maximize the average level of utility of currently living agents. A ban on child labor decreases children's income and generates an increase in parental transfers bringing their levels closer to the optimum, raising children's welfare as well as average welfare in the short run and in the long run. Moreover, the inability to work allows children to allocate more time to education, and it leads to an increase in human capital. Besides, to increase transfers, parents decrease savings and hence physical capital accumulation. When prices are flexible, these effects diminish the positive welfare impact of the ban on child labor. (JEL D91, E21)     

A heuristic for inventory management of slow-moving items

Abstract. The traditional approach in the study of inventory systems is to give more importance to items whose demands are either large or very difficult to forecast, discounting the importance of inventory items with small demand. The objective of this paper is to present a simple and practical heuristic to the slow-moving items problem. First we provide insight into previous work in this area and also give a brief outline of classical models in stochastic inventory theory. Then we present the proposed approach and detail the heuristic. We summarize the paper with an analysis of the simulation results and finish with the conclusions that are drawn from the results.