Name
Abstract | ||
|---|---|---|
Multilevel programming is developed for modeling decentralized decision-making processes. For different management requirements and risk tolerances of different-level decision-makers, the decision-making criteria applied in different levels cannot be always the same. In this paper, a hybrid multilevel programming model with uncertain random parameters based on expected value model (EVM) and dependent-chance programming (DCP), named as EVM–DCP hybrid multilevel programming, is proposed. The corresponding concepts of Nash equilibrium and Stackelberg–Nash equilibrium are given. For some special case, an equivalent crisp mathematical programming is proposed. An approach integrating uncertain random simulations, Nash equilibrium searching approach and genetic algorithm is designed. Finally, a numerical experiment of uncertain random supply chain pricing decision problem is given. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/s10845-014-0985-5 | J. Intelligent Manufacturing |
Keywords | Field | DocType |
Multilevel programming,Uncertain variable,Uncertain random programming,Dependent-chance programming,Expected value model | Decision problem,Mathematical optimization,Computer science,Multilevel programming,Expected value,Artificial intelligence,Supply chain,Nash equilibrium,Machine learning,Genetic algorithm,Random parameters,Special case | Journal |
Volume | Issue | ISSN |
28 | 3 | 0956-5515 |
Citations | PageRank | References |
3 | 0.42 | 17 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hua Ke | 1 | 104 | 13.34 |
| Junjie Ma | 2 | 148 | 15.24 |
| Guangdong Tian | 3 | 158 | 13.86 |