Stochastic Programming Methods Based on Synthesizing Effect Function and Its Application for the Measures Program of Oilfield

In this paper, by analyzing the essential characteristic of stochastic programming and the deficiencies of the existing methods, we propose the concept of synthesizing effect function for processing the objective function and constraints, and further we give an axiomatic system for synthesizing effect function. Finally, we establish a general solution model based on synthesizing effect function for stochastic programming problem, and analyze the model through an example. All the results indicate that our method not only includes the existing methods for stochastic programming, but also effectively merge the decision preferences into the solution, so it can be widely used in many fields such as complicated system optimization and artificial intelligence etc.