Abstract
A multi-objective freight train routing problem with fuzzy information is investigated in this article. To handle the fuzziness in the railway transportation system, the measure M λ (i.e. the convex combination of a possibility measure and a necessity measure) is first introduced. Then, a min-max chance-constrained programming model is constructed to obtain optimal train routing plans. In order to solve the model, a potential route algorithm, fuzzy simulation and tabu search algorithm are integrated as a hybrid algorithm. Finally, some numerical experiments are performed to show the applications of the model and the algorithm.
| Original language | English |
|---|---|
| Pages (from-to) | 1289-1309 |
| Number of pages | 21 |
| Journal | Engineering Optimization |
| Volume | 43 |
| Issue number | 12 |
| DOIs | |
| Publication status | Published - 1 Dec 2011 |
| Externally published | Yes |
Keywords
- fuzzy variable
- M measure
- tabu search algorithm
- train routing problem
Fingerprint
Dive into the research topics of 'A weighted min-max model for balanced freight train routing problem with fuzzy information'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver