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3345. A parallel Benders' decomposition algorithm for solving the integrated long-haul and local vehicle routing problem
Invited abstract in session TA-30: Parallel Solvers, stream Software for Optimization.
Tuesday, 8:30-10:00Room: 064 (building: 208)
Authors (first author is the speaker)
| 1. | Stephen Maher
|
| GAMS Software GmbH | |
| 2. | Junko Hosoda
|
| Research and Development Group, Hitachi, Ltd. | |
| 3. | Yuji Shinano
|
| Optimization, Zuse Institue Berlin |
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 using general purpose solvers. As such, only very small instances of this problem can be solved without the use of decomposition techniques. We propose a Benders' decomposition approach that identifies transportation network design in the master problem and then solves the integrated long-haul and local vehicle routing problem in the subproblem. The Benders' decomposition approach is used to solve a relaxation within a parallelisation framework that concurrently solves an iterative algorithm for finding high quality primal solutions. The results will show that applying Benders' decomposition increases the scale of problems that can solved and improves the upper and lower bounds that can be achieved.
Keywords
- Supply Chain Management
- Parallel Algorithms and Implementation
Status: accepted
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