Article ID: | iaor19982987 |
Country: | United Kingdom |
Volume: | 34 |
Issue: | 12 |
Start Page Number: | 89 |
End Page Number: | 104 |
Publication Date: | Dec 1997 |
Journal: | Computers & Mathematics with Applications |
Authors: | Liu Baoding |
Keywords: | artificial intelligence, simulation, stochastic processes |
This paper provides a theoretical framework of dependent-chance programming, as well as dependent-chance multiobjective programming and dependent-chance goal programming which are new types of stochastic optimization. A stochastic simulation based genetic algorithm is also designed for solving dependent-chance programming models.