Difference between revisions of "Using Deep Q-Learning (Alpha-Go algorithm) to solve routing problems in warehouse logistics"
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{{StudentProjectTemplate | {{StudentProjectTemplate | ||
| − | |Summary= | + | |Summary=Solving the famous vehicle-routing problem using Deep Q-Learning |
|Keywords=vehicle routing problem, Reinforcement learning | |Keywords=vehicle routing problem, Reinforcement learning | ||
|Supervisor=Jennifer David, Thorsteinn Rögnvaldsson, | |Supervisor=Jennifer David, Thorsteinn Rögnvaldsson, | ||
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|Status=Open | |Status=Open | ||
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| + | For a group of robots or forklifts involved in warehouses, Sony Mobile in Lund has a Masters Thesis project. The aim is to generate paths/routes for all vehicles according to a pre-determined schedule without any path-conflicts and schedule conflicts. This is an NP-hard problem termed as vehicle routing problem and has been solved using heuristic approaches. Here, we try to use Deep Q learning to solve it. | ||
Latest revision as of 17:00, 19 October 2018
| Title | Using Deep Q-Learning (Alpha-Go algorithm) to solve routing problems in warehouse logistics |
|---|---|
| Summary | Solving the famous vehicle-routing problem using Deep Q-Learning |
| Keywords | vehicle routing problem, Reinforcement learning |
| TimeFrame | |
| References | |
| Prerequisites | |
| Author | |
| Supervisor | Jennifer David, Thorsteinn Rögnvaldsson |
| Level | Master |
| Status | Open |
For a group of robots or forklifts involved in warehouses, Sony Mobile in Lund has a Masters Thesis project. The aim is to generate paths/routes for all vehicles according to a pre-determined schedule without any path-conflicts and schedule conflicts. This is an NP-hard problem termed as vehicle routing problem and has been solved using heuristic approaches. Here, we try to use Deep Q learning to solve it.
