2210. A parallelisation framework for solving challenging integrated long-haul and local vehicle routing problems
Invited abstract in session WB-43: Parallelize now!, stream Software for Optimization.
Wednesday, 10:30-12:00Room: Newlyn GR.07
Authors (first author is the speaker)
| 1. | Stephen Maher
|
| GAMS Software GmbH | |
| 2. | Yuji Shinano
|
| Optimization, Zuse Institue Berlin | |
| 3. | Takafumi CHIDA
|
| 4. | Akane Seto
|
| Research & Development Group, Hitachi, Ltd. |
Abstract
The integrated long-haul and local vehicle routing problem with an adaptive transportation network is a very challenging optimisation problem. The adaptive nature of the transportation network means that the resulting optimisation problem is extremely large and difficult to solve directly using general purpose solvers. As such, the best approach for finding high quality solutions is to use heuristics combined with a branch-and-bound algorithm. Our research has developed a parallelisation framework that concurrently executes heuristic and exact approached to find high-quality solutions to the integrated long-haul and local vehicle routing problem. Within the parallelisation framework we have attempted to solve the complete problem directly using a MIP solver and by applying Benders' decomposition. The results will show that the use of parallelisation and applying Benders' decomposition increases the scale of problems that can solved and improves the upper and lower bounds that can be achieved.
Keywords
- Parallel Algorithms and Implementation
- Supply Chain Management
- Software
Status: accepted
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