Estimation of population mean in presence of random non response in two-stage cluster sampling

The present investigation addresses the problem of estimating a finite population mean in two-phase cluster sampling in presence of random non response situations. Utilizing information on an auxiliary variable, regression type estimators has been proposed. Effective imputation techniques have been suggested to deal with the random non response situations. The properties of the proposed estimation strategies have been studied for different cases of random non response situations in practical surveys. The superiority of the suggested methodology over the natural sample mean estimator of population mean has been established through empirical studies carried over the data sets of natural population and artificially generated population.     

Multi-product lot scheduling with backordering and shelf-life constraints

In this paper, we revisit the economic lot scheduling problem (ELSP), where a family of products is produced on a single machine, or facility, on a continual basis. Our focus is on the determination of a feasible production schedule, including the manufacturing batch size of each item. We assume that total backordering is permissible and that each of the products has a limited post-production shelf life. Several studies examining this problem have suggested a rotational common cycle approach, where each item is produced exactly once every cycle. To ensure schedule feasibility, we resort to the technique of reducing individual production rates and allow the flexibility of producing any item more than once in every cycle, in conjunction with appropriate timing adjustments. In order to solve this more generalized model, which is NP hard, we suggest a two-stage heuristic algorithm. A numerical example demonstrates our solution approach.     

A JOINT ECONOMIC-LOT-SIZE MODEL FOR PURCHASER AND VENDOR

In a typical purchasing situation, the issues of price, lot sizing, etc., usually are settled through negotiations between the purchaser and the vendor. Depending on the existing balance of power, the end result of such a bargaining process may be a near-optimal or optimal ordering policy for one of the parties (placing the other in a position of significant disadvantage) or, sometimes, inoptimal policies for both parties. This paper develops a joint economic-lot-size model for a special case where a vendor produces to order for a purchaser on a lot-for-lot basis under deterministic conditions. The focus of this model is the joint total relevant cost. It is shown that a jointly optimal ordering policy, together with an appropriate price adjustment, can be beneficial economically for both parties or, at the least, does not place either at a disadvantage.     

Measuring the economic impacts of recent oil price shocks on oil-dependent economy: evidence from Malaysia

This paper examines the economy-wide impacts of recent oil price shocks on the Malaysian economy. To achieve this objective, an integrated methodological framework that combines econometric and input–output models is utilized to assess the impacts of an oil price shock on tax revenues, employment, labor income and gross domestic product (GDP). Our results reveal that the recent oil price shocks significantly affects these macroeconomic variables. The decline in oil prices from 2015 to 2016 reduces tax revenues by 10.5%, lower GDP by 1.9% and increases the unemployment rate by 0.3%. As such, the sharp crunch in oil prices serves as a reminder to policymakers on the vulnerability inherent in overreliance on oil exports and the urgent need to diversify the economy.