Article ID: | iaor20083439 |
Country: | Netherlands |
Volume: | 53 |
Issue: | 3 |
Start Page Number: | 433 |
End Page Number: | 453 |
Publication Date: | Oct 2007 |
Journal: | Computers & Industrial Engineering |
Authors: | Liu Baoding, Peng Jin |
Keywords: | heuristics: genetic algorithms |
The emphasis of this paper is to introduce a novel concept of birandom variable and to exhibit the framework of birandom programming. The so-called birandom variable is a measurable mapping from a probability space to a collection of random variables. Based on this definition, the expected value operator of birandom variable and chance measures of birandom event are further introduced. As a generalized scenario of stochastic programming, a spectrum of birandom programming models are developed to deal with birandom systems. To solve the proposed models, birandom simulations are presented and then a hybrid intelligent algorithm is designed by embedding neural networks into genetic algorithm. Finally, some numerical experiments are provided to illustrate the effectiveness of the algorithm.