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.     

Impacts of back to the land policies

A model of rural-urban migration is formulated for some developing economies. The emphasis is on decision making under uncertainty by the rural household. An income effect which is related to some hypotheses concerning behavior of the household towards risk is included along with a conventional price effect in the model. The impact of back to the land policies on the rate of migration in this model differs from the results of some models by Todaro and Harris and several refinements to the Harris-Todaro model as are nicely summed up in an article entitled ‘Internal Migration and Economic Development: An Overview’ by Lucas. The principal result of this analysis lies in its challenge to the conventional wisdom that back to the land policies necessarily dampen rural exodus.     

Livestock as Insurance and Social Status: Evidence from Reindeer Herding in Norway

The theory of livestock as a buffer stock predicts that agropastoralists facing substantial risks will typically use liquid assets such as livestock for self-insurance to smooth consumption. This paper examines this hypothesis for reindeer herders in Norway where the herders, in contrast to pastoralists in, say, sub-Saharan Africa, face well-functioning credit markets. Using survey data including slaughter responses to a hypothetical meat price increase, we test whether keeping reindeer as insurance against risks affects the slaughter response. Furthermore, we examine whether status motives for keeping large herds affect the harvest response to a changing slaughter price. As a background to the empirical analysis, a stochastic bioeconomic model describing Saami reindeer herding is formulated.     

A structural Bayesian VAR for model-based fan charts

Inflation forecast uncertainty is of importance for a wide range of agents in the economy, central banks in particular. Ways to describe and account for this uncertainty in a consistent manner have received increasing attention of late, in part due to the growing number of inflation-targeting central banks. This article develops a large structural VAR for the Swedish economy and estimates it in a Bayesian framework. The methodology permits not only structural interpretation and analysis but offers a natural way to formalize forecast uncertainty, as the posterior predictive density from the model has the interpretation of a fan chart.     

REGIONAL AND SECTORAL DISAGGREGATION OF MULTI-REGIONAL INPUT–OUTPUT TABLES – A FLEXIBLE ALGORITHM

A common shortcoming of available multi-regional input–output (MRIO) data sets is their lack of regional and sectoral detail required for many research questions (e.g. in the field of disaster impact analysis). We present a simple algorithm to refine MRIO tables regionally and/or sectorally. By the use of proxy data, each MRIO flow in question is disaggregated into the corresponding sub-flows. This downscaling procedure is complemented by an adjustment rule ensuring that the sub-flows match the superordinate flow in sum. The approximation improves along several iteration steps. The algorithm unfolds its strength through the flexible combination of multiple, possibly incomplete proxy data sources. It is also flexible in a sense that any target sector and region resolution can be chosen. As an exemplary case we apply the algorithm to a regional and sectoral refinement of the Eora MRIO database.