Study on Stochastic Programming Methods Based on Synthesizing Effect

Stochastic programming is a well-known optimization problem in resource allocation, optimization decision etc. 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 (denoted by BSE-SGM for short) 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.