Risk analysis of production system, while the actual and appropriate data is not available, will cause wrong system parameters prediction and wrong decision making. In uncertainty condition, there are no appropriate measures for decision making. In epistemic uncertainty, we are confronted by the lack of data. Therefore, in calculating the system risk, we encounter vagueness that we have to use ...

We apply nonparametric panel data kernel regression to investigate production risk, output price uncertainty, and risk attitudes of Polish dairy farms based on a firm-level unbalanced panel data set that covers the period 2004–2010. We compare different model specifications and different approaches for obtaining firm-specific measures of risk attitudes. We found that Polish dairy farmers are ri...

The mine production planning defines a sequence of block extraction to obtain the highest NPV under a number of constraints. Mathematical programming has become a widespread approach to optimize production planning, for open pit mines since the 1960s. However, the previous and existing models are found to be limited in their ability to explicitly incorporate the ore grade uncertainty into the p...

perishability of blood products as well as uncertainty in demand amounts complicate the management of blood supply for blood centers. this paper addresses a mixed-integer linear programming model for blood platelets production planning while integrating the processes of blood collection as well as production/testing, inventory control and distribution. whole blood-derived production methods for...

The traditional production planning model based upon the famous linear programming formulation has been well known in the literature. The consideration of uncertainty in manufacturing systems supposes a great advance. Models for production planning which do not recognize the uncertainty can be expected to generate inferior planning decisions as compared to models that explicitly account the unc...

In this paper, absorbing Markov chain models are developed to determine the optimum process mean levels for both a single-stage and a serial two-stage production system in which items are inspected for conformity with their specification limits. When the value of the quality characteristic of an item falls below a lower limit, the item is scrapped. If it falls above an upper limit, the item is ...

F often have to make their production decisions under conditions of demand uncertainty. This is especially true for product categories such as automobiles and technology goods where the lead time needed for manufacturing forces firms to make production decisions well in advance of the selling season. Once the firm has produced the goods, the available production volume affects the firm’s subseq...

in this study, a new stochastic model is proposed to deal with a multi-product, multi-period, multi-stage, multi-site production and transportation supply chain planning problem under demand uncertainty. a two-stage stochastic linear programming approach is used to maximize the expected profit. decisions such as the production amount, the inventory level of finished and semi-finished product, t...

This paper presents a theoretical model in which the stock growth rate of durable goods has stochastic fluctuation over time. It concludes that a social planner increases the expected percentage rate of production since uncertainty increases the user cost from consumer’s point view.

This paper constructs a model economy to explain how uncertainty shocks can cause business cycle fluctuations. In the model, during times of high uncertainty, the representative agent, due to risk aversion motives, moves resources from a high risk/high return production process to a low risk/low return production process. High uncertainty thus causes the firm level technology frontier to endoge...