The Moderate Operation Scales of Apples Based on Output, Profit, and Unit Production Costs in the Shaanxi Province of China

In the Shaanxi province, small and scattered plots impede an increase in the efficiency of apple production. Developing a moderate operation scale is a proper tool to solve inefficiencies in apple production, as it enables improving the factor allocation efficiency, resulting in higher yields, higher profit, or lower production costs. However, the moderate operation scales, based on output, profit, and production costs, may be different. This paper aimed to evaluate the moderate operation scale of apples from three perspectives of increasing yields and profits and reducing unit production cost. The study was based on survey data collected from 661 randomly selected apple farmers in eight counties of the Shaanxi province, China. The collected data were analyzed quantitatively by the input-output model, the net profit model, and unit production cost model. The findings show that: (1) The moderate operation scale oriented to increasing apple yields in the Shaanxi province should be 0.87–1.53 ha. (2) The moderate operation scale oriented to increasing the net profit of farmers in the Shaanxi province should be over 1.53 ha. (3) The moderate operation scale oriented to reducing the unit cost of apple production in the Shaanxi province should be 0.20–0.53 ha. The study provides evidence that policymakers should grasp the balance point and find the intersection of the operation scale based on output, profit, and unit production cost when guiding apple growers to carry out the moderate scale. We propose that 0.87–1.53 ha may be a suitable operation scale for apple production in the Shaanxi province at the current stage.

A Feasibility Study of Cellulosic Isobutanol Production—Process Simulation and Economic Analysis

Renewable liquid biofuels for transportation have recently attracted enormous global attention due to their potential to provide a sustainable alternative to fossil fuels. In recent years, the attention has shifted from first-generation bioethanol to the production of higher molecular weight alcohols, such as biobutanol, from cellulosic feedstocks. The economic feasibility of such processes depends on several parameters such as the cost of raw materials, the fermentation performance and the energy demand for the pretreatment of biomass and downstream processing. In this work, two conceptual process scenarios for isobutanol production, one with and one without integrated product removal from the fermentor by vacuum stripping, were developed and evaluated using SuperPro Designer®. In agreement with previous publications, it was concluded that the fermentation titer is a crucial parameter for the economic competitiveness of the process as it is closely related to the energy requirements for product purification. In the first scenario where the product titer was 22 g/L, the energy demand for downstream processing was 15.8 MJ/L isobutanol and the unit production cost of isobutanol was $2.24/L. The integrated product removal by vacuum stripping implemented in the second scenario was assumed to improve the isobutanol titer to 50 g/L. In this case, the energy demand for the product removal (electricity) and downstream processing were 1.8 MJ/L isobutanol and 10 MJ/L isobutanol, respectively, and the unit production cost was reduced to $1.42/L. The uncertainty associated with the choice of modeling and economic parameters was investigated by Monte Carlo simulation sensitivity analysis.

A fuzzy inventory model with unit production cost, time depended holding cost, with-out shortages under a space constraint: a parametric geometric programming approach

In this paper, an Inventory model with unit production cost, time depended holding cost, with-out shortages is formulated and solved. We have considered here a single objective inventory model. In most real world situation, the objective and constraint function of the decision makers are imprecise in nature, hence the coefficients, indices, the objective function and constraint goals are imposed here in fuzzy environment. Geometric programming provides a powerful tool for solving a variety of impreciseoptimization problem. Here we have used nearest interval approximation method to convert a triangular fuzzy number to an interval number then transform this interval number to a parametric interval-valued functional form and solve the parametric problem by geometric programming technique. Here two necessary theorems have been derived. Numerical example is given to illustrate the model through this Parametric Geometric-Programming method.