Application Of Stochastic Programming Research Articles

A study of economic efficiency of Iranian farmers in Ramjerd district: an application of stochastic programming

AbstractAn extension of utility‐efficient programming to the non‐linear discrete stochastic programming method was developed and used in the analysis of the economic efficiency of a sample of farmers in Iran. The results indicate that it would be feasible to increase substantially farmers' total net revenue by increasing their economic efficiency in terms of technical and allocative efficiencies. The study further suggested that risk aversion plays an important role in farmers' behaviour. The sample farmers are risk averse and hence are likely to trade higher expected profits for lower risk. Understanding this characteristic is important for interventions intended to raise farm productivity and efficiency.

Applications of stochastic programming under incomplete information

The main part of the paper (Section 3) provides an overview of case studies based on stochastic programming models in which reality of incomplete information about distribution of random parameters is clearly accepted and treated. Also, several techniques of scenario generation are surveyed in this context. Basic ideas of various approaches to stochastic programming models under incomplete information are briefly explained on illustrative examples in Section 2.

Risk preference and optimal crop combinations in upland Java, Indonesia: an application of stochastic programming

ABSTRACTA stochastic programming model was used to evaluate the economic performance of a soybean‐based farming system in upland Java. The model incorporates farmers' risk preferences, revenue fluctuations and resources restrictions. The results show that (1) changes in risk preference do affect the optimal crop combination, and (2) the typical cropping pattern is rational under the present level of the farmers' risk preference estimated in the study site.

Risk preference and optimal crop combinations in upland Java, Indonesia: An application of stochastic programming

A stochastic programming model was used to evaluate the economic performance of a soybean-based farming system in upland Java. The model incorporates farmers' risk preferences, revenue fluctuations and resources restrictions. The results show that (1) changes in risk preference do affect the optimal crop combination, and (2) the typical cropping pattern is rational under the present level of the farmers' risk preference estimated in the study site.

Risk Preference and Adoption of New Technology under Uncertainty: An Application of Stochastic Programming to a Vegetable Farming System in Chiba, Japan

Risk Preference and Adoption of New Technology under Uncertainty: An Application of Stochastic Programming to a Vegetable Farming System in Chiba, Japan

Optimizing Resource Acquisition Decisions by Stochastic Programming

This paper reports on the application of stochastic programming with recourse to strategic planning decisions regarding resource acquisition. A resource directed decomposition method, which simultaneously exploits stochastic programming and mixed integer programming model structures, is proposed. Computational experience with the method applied to fuel contract and plant construction decisions faced by an electric utility is presented.

Stochastic programming in production planning: a case with none‐simple recourse

Abstract In modeling real world planning problems as optimization programs the assumption that all parameters are known with certainty is often more seriously violated than the assumption that the objective function and the constraints can be approximated sufficiently accurate by lineair functions. In this paper we discuss the concrete application of stochastic programming to a multiperiod production planning problem in which the demand for the products during the various periods is assumed stochastic with known probability distribution. Since the resulting stochastic program does not possess the property of “simple” recourse no direct use can be made of existing methods that have been proposed in literature for solving problems of this type.