Abstract
A programming method, termed as balanced programming between target and chance, is developed. Based on the all-around information about the effective decision front curve (EDFC) of the problems concerned, this method can maximize the utility of a decision-making problem through weighing the quantity relationships and comparing the changing velocity along the EDFC between the target profit and the realization chance. The method can solve stochastic optimization problems in a more rational, flexible, and easy-to-use way, and avoid conflicts among the expected value model, chance-constrained programming and dependent chance programming. A numerical example shows the effectiveness and main features of the proposed method.
| Original language | English |
|---|---|
| Pages (from-to) | 1641-1646 |
| Number of pages | 6 |
| Journal | Kongzhi yu Juece/Control and Decision |
| Volume | 24 |
| Issue number | 11 |
| Publication status | Published - Nov 2009 |
Keywords
- Balanced programming between target and chance(BPTC)
- Bidding strategies
- Chance-constrained programming(CCP)
- Dependent chance programming(DCP)
- Expected value model(EVM)
ASJC Scopus subject areas
- Control and Systems Engineering
- Software
- Control and Optimization
- Artificial Intelligence